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Background: This study explores recent cohort trends in cognitive performance among older Europeans from 2007 to 2017, addressing three key questions: (1) Did cognitive performance improve universally and across the performance distribution during this period? (2) Did these improvements occur across educational levels and for both men and women? (3) Can established risk factors explain these performance gains? Methods: Using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) across 12 European countries, we assessed immediate recall, delayed recall, and verbal fluency in individuals aged 60 to 94 in both 2007 and 2017 (n = 32 773). Differences between the two time points were estimated with linear mixed effects regression models and quantile regression. Results: Cognitive performance improved in all age groups, across educational levels, and for both men and women between 2007 and 2017. Notably, improvements were more pronounced at the upper end of the performance distribution for delayed recall and verbal fluency. Education explained approximately 20% of the observed improvements. Risk factors did not explain the observed improvements. Conclusions: European cohorts of both younger-old and older adults continue to exhibit improvements in cognitive performance. Variation in the size of the cohort improvements across the performance distributions in delayed recall and in verbal fluency may contribute to growing inequalities in cognitive outcomes. Future research should further investigate the potential heterogeneity in cognitive performance gains. Trial registration: Not applicable. [ABSTRACT FROM AUTHOR]

Analysis of phylogenetic trees has become an essential tool in epidemiology. Likelihood-based methods fit models to phylogenies to draw inferences about the phylodynamics and history of viral transmission. However, these methods are often computationally expensive, which limits the complexity and realism of phylodynamic models and makes them ill-suited for informing policy decisions in real-time during rapidly developing outbreaks. Likelihood-free methods using deep learning are pushing the boundaries of inference beyond these constraints. In this paper, we extend, compare, and contrast a recently developed deep learning method for likelihood-free inference from trees. We trained multiple deep neural networks using phylogenies from simulated outbreaks that spread among 5 locations and found they achieve close to the same levels of accuracy as Bayesian inference under the true simulation model. We compared robustness to model misspecification of a trained neural network to that of a Bayesian method. We found that both models had comparable performance, converging on similar biases. We also implemented a method of uncertainty quantification called conformalized quantile regression that we demonstrate has similar patterns of sensitivity to model misspecification as Bayesian highest posterior density (HPD) and greatly overlap with HPDs, but have lower precision (more conservative). Finally, we trained and tested a neural network against phylogeographic data from a recent study of the SARS-Cov-2 pandemic in Europe and obtained similar estimates of region-specific epidemiological parameters and the location of the common ancestor in Europe. Along with being as accurate and robust as likelihood-based methods, our trained neural networks are on average over 3 orders of magnitude faster after training. Our results support the notion that neural networks can be trained with simulated data to accurately mimic the good and bad statistical properties of the likelihood functions of generative phylogenetic models. [ABSTRACT FROM AUTHOR]

E-commerce plays a crucial role in the digital economy. E-commerce can reduce costs and boost economic growth. Therefore, the global rate of E-commerce is increasing very fast, which has implications for the digital economy. This study analyses the impact of e-commerce on environmental sustainability. The empirical analysis employed OLS, 2SLS, GMM, and panel quantile regression methods using panel data of 10 European economies spanning over 2002–2019. Carbon emissions and GHG emissions measure environmental sustainability. The results from OLS, 2SLS and GMM show that e-commerce negatively impacts carbon emissions. The panel quantile regression results also show that e-commerce negatively impacts carbon emissions at the middle and higher quantiles. This study recommends that environmental sustainability programs pay attention to policies encouraging e-commerce. [ABSTRACT FROM AUTHOR]

European power markets are in the midst of unprecedented changes, with a record-breaking surge in energy prices. This paper investigates the impact of the green transition on the level and volatility of wholesale electricity prices at a granular level, using monthly observations for a panel of 24 European countries over the period 2014–2021 and alternative estimation methods including a panel quantile regression approach. We find that renewable energy is associated with a significant reduction in wholesale electricity prices in Europe, with an average impact of 0.6 percent for each 1 percentage points increase in renewable share. We also find evidence for a nonlinear effect—that is, higher the share of renewables, the greater its effect on electricity prices. On the other hand, while quantile estimation results are mixed with regards to the impact of renewables on the volatility of electricity prices, we obtain evidence that renewable energy has a negative effect on volatility at the highest quantiles. Overall, our analysis indicates that policy reforms can help accelerate the green transition while minimizing the volatility in electricity prices. [ABSTRACT FROM AUTHOR]

In this paper, we analyse the impact of gender equality in managerial positions on wages and the gender wage gap in 22 European countries. We draw on the employer–employee microdata from the European Structure of Earnings Survey (E-SES) for the year 2018, which allows us to include firm fixed effects in our econometric specifications, thus controlling for both observed and unobserved heterogeneity at the firm level. The analysis is carried out not only at the mean but also across the wage distribution through unconditional quantile regressions. The results on the impact of gender equality in management on wages are mixed. However, we find that gender equality has a predominantly positive effect in the upper part of the wage distribution, and a negative effect in the middle and lower parts. The results on the impact on the gender wage gap show that in many cases, a more gender-equal management reduces the gender wage gap. Furthermore, gender equality in management reduces the gender wage gap mainly in the middle and lower part of the wage distribution. [ABSTRACT FROM AUTHOR]

This paper investigates how housing prices respond to economic, financial and demographic conditions in emerging markets in Europe. We use quarterly data covering 10 countries over the period 1998–2022 and implement a panel quantile regression approach to obtain a granular analysis of real estate markets. Overall, economic, financial and demographic developments explain real house price growth in emerging Europe, with income growth having the most significant impact. Quantile regression estimations show that income growth matters more for higher quantiles of the property market. We also find that an increase in short-term or long-term interest rates has a price-dampening impact, indicating that a higher cost of borrowing is associated with lower real house price growth. These results indicate that the downturn in house prices could deepen with the looming economic recession and soaring interest rates. [ABSTRACT FROM AUTHOR]

Environmental sustainability concerns are growing worldwide. Reducing carbon dioxide (CO2) emissions is crucial to combating global warming and reaching sustainable global economic development. Many recent studies have focused on key indicators of CO2 emissions, but less consideration has been given to associated factors such as renewable energy and human capital. This article applies the two-step system FOD-GMM (Forward-Orthogonal Deviations-Generalized Method of Moments) to estimate the role of renewable energy and human capital in reducing environmental degradation in Europe and Central Asia. The results reveal that renewable energy consumption and human capital have a significant negative impact on CO2 emissions in the EU and Central Asian countries, government efficiency has a positive effect on CO2 emissions, and economic development has a neutral effect, confirming the strong role of renewable energy and human capital in reducing CO2 emissions in EU and Central Asian countries. The role of human capital and renewable energy in promoting CO2 reduction should be fully utilized. Policymakers should develop infrastructure for renewable energy and education to support the decrease in CO2 emissions in Europe and Central Asia. [ABSTRACT FROM AUTHOR]

We appraise the effects of institutional quality on public spending for a set of 27 European countries and 18 Euro‐area economies over the 1996–2017 period. While institutions play a weak role in affecting spending once the fixed‐effects model is employed, the application of the quantile regression indicates that improved institutional quality mitigates public spending, although the effects crucially depend on the distribution of public expenditure and the sample examined. For both the Euro‐area sample and the full sample, we show that better quality of institutions reduces public spending, although the effects become less significant the higher the levels of public spending. Further, for the Euro‐area sample, institutions appear to have a stronger role in mitigating public spending. Several robustness tests confirm our findings. [ABSTRACT FROM AUTHOR]

Purpose: Since competitiveness is crucial in international trade, this paper contributes to the literature by interrogating the information and communication technology (ICT)-trade nexus on competitiveness in Eastern and Western European countries. Does ICT usage promote or hinder the impact of trade openness on competitiveness? This study attempts to answer two questions: (1) is the interaction of trade and ICT significant in promoting competitiveness? (2) Is the effect significantly different by European classification? Design/methodology/approach: With data on 17 European countries from 2007 to 2020 and using mobile phones and fixed telephone usage as ICT indicators, the study engages the bootstrapped ordinary least squares (BOLS) and method of moments quantile regression (MM-QR) techniques to probe the discourse. Findings: The empirical findings reveal that (1) the interaction of trade and ICT boost competitiveness; (2) the effect of mobile phone is consistent across the full, East, and West European samples; (3) the interaction effect is also significant across the conditional distribution of competitiveness and (4) mobile phones and fixed broadband usage reveal "leapfrog" effect across the quantiles. Overall, the study submits that ICT usage will enhance the impact of trade, and thus, ICT is a critical enabler of competitiveness in Europe; policy recommendations were discussed. Originality/value: To the best of the authors' knowledge, this is the first study examining the interaction effect of trade openness and ICT usage on competitiveness in Europe. In other words, the authors attempt to analyze how ICT usage influences trade-competitiveness dynamics. To fill the gap in the literature, the authors' use a sample of 17 European countries from 2007 to 2020. The variables of interest are the competitiveness index, trade openness, and four ICT indicators (mobile phone, fixed telephone subscriptions, fixed telephone subscriptions, and Internet users). [ABSTRACT FROM AUTHOR]

This study critically examines the health-environment discourse and uses infant and under-5 mortality rates, carbon emissions, and non-renewable energy to investigate the inherent associations. We argue that the concentration of greenhouse gas emissions is considered to increase and can undermine the access to basic resources necessary for leading a healthy life, such as access to food, water, health, and the environment. Environmental health is closely linked to human health. The world is witnessing a substantial increase in greenhouse gas emissions, which pose a significant threat to both environment and human health. Hence, this study contributes to the discourse with unbalanced panel data on 46 European countries from 2005 to 2015 to investigate the impact of carbon emissions and non-renewable energy on infant and under-5 mortality rates. Consistent findings from static and dynamic analyses reveal that (1) carbon emission is positively associated with mortality rate; (2) non-renewable energy shows a significant negative relationship; (3) persistency in mortality rates exists; (4) positive (negative) association of emissions (non-renewable energy) dwindles (increases) in absolute value at higher distributions of mortality rates; and (5) Euro Union countries show lower mortality rates relative to non-Euro Union members. Policy recommendations are discussed. [ABSTRACT FROM AUTHOR]

Since curbing the upward trend of energy consumption has become a global pursuit in achieving environmental sustainability, macroeconomic factors such as energy transition and international tourism may be of crucial importance in mitigating environmental degradation. However, the combined role of economic welfare, population, international tourism, and energy transition towards mitigating environmental degradation has not been investigated extensively. In this regard, this study looks at the combined interplay between these variables for a panel of ten southeastern Europe (SEE) countries, covering the period of 1997–2018 under the umbrella of the environmental Kuznets curve (EKC) phenomenon. Two indicators of environmental degradation, namely, ecological footprint and carbon intensity, were used in this study. The ordinary least squares (OLS) regression with Driscoll–Kraay (DK) and the panel Method of Moments Quantile Regression (MMQR) with fixed effects were used to disclose the following outcomes: firstly, the environmental degradation–economic welfare nexus firmly established an inverted U-shaped relationship, thereby depicting the validity of the EKC hypothesis. Secondly, energy transition and international tourism manifest negative effects: they induce environmental degradation. Thirdly, the impact of the population is positive but not significant. Given the empirical outcomes, energy transition and international tourism are proposed as critical to mitigating the environmental degradation of the inspected sample of countries. [ABSTRACT FROM AUTHOR]

While long‐term changes in measures of central tendency of climate elements, that is, mean temperature, are well acknowledged, studies of trends in measures of their variability are much less common. This is despite the fact that trends in variability can have higher effect on climate extremes than trends in mean. Here, four measures of intraseasonal variability are examined: (a) standard deviation of mean daily temperature, (b) the range between the 90th and 10th quantile of mean daily temperature, (c) mean absolute value of day‐to‐day temperature change, and (d) one‐day lagged temporal autocorrelation. ECA&D daily data from 168 stations and linear regression method are utilized to calculate trends of these characteristics in period from 1961 to 2018. Significant trends (positive and negative) are revealed with substantial differences between seasons, regions and measures. The most considerable decreases in temperature variability were recorded in winter, for temporal autocorrelation in eastern Europe and for variance‐based measures in northern Europe. For example, the standard deviation has decreased by more than 10% in the Arctic Ocean. This can indicate a decrease in the frequency of cold extremes in Scandinavia. On the contrary, increasing persistence may suggest a greater likelihood of cold extremes in the East European Plain. Increases in variability prevail only in summer, but not for all measures and not as clearly as decreases in winter. Trends in temporal autocorrelation and day‐to‐day change appear to be sensitive to data issues, such as inhomogeneities and changes in observational procedures. [ABSTRACT FROM AUTHOR]

Background Physical activity may sustain the physical aspect of work ability despite health problems such as musculoskeletal disorders and anxiety, which are the most prevalent work-related health problem in Europe. Aims To evaluate the association of Finnish municipal workers' accelerometer-measured physical activity, sedentary behaviour, and cardiorespiratory and muscular fitness with their sickness absence levels, perceived work ability and health-related quality of life. Methods In connection with a randomized controlled trial recruiting 185 municipal workers, the authors performed baseline data analysis utilizing quantile regression to examine relationships between the outcome variables (all-cause sickness absence for 6 months, perceived work ability and health-related quality of life) and cardiorespiratory fitness, muscular fitness, and physical activity, and sedentary behaviour. All results were adjusted for age, sex and education level. Results The median duration of all-cause sickness absence over the preceding 6 months was lowest among participants with high cardiorespiratory fitness relative to the lowest tertile (2.0 versus 6.0 days; P < 0.05), and the highest perceived work ability was found among those with high or moderate cardiorespiratory fitness as compared to the lowest tertile (8.0 versus 7.0; P < 0.001). Moderate-to-vigorous physical activity correlated positively with the physical component of health-related quality of life (P < 0.01) and with a high cardiorespiratory-fitness level (P < 0.05). Conclusions High cardiorespiratory fitness was associated with decreased all-cause sickness absence days and improved work ability among municipal workers. [ABSTRACT FROM AUTHOR]

For banks, credit lines play an important role exposing both liquidity and credit risk. In the advanced internal ratings‐based approach, banks are obliged to use their own estimates of exposure at default using credit conversion factors. For volatile segments, additional downturn estimates are required. Using the world's largest database of defaulted credit lines from the US and Europe and macroeconomic variables, we apply a Bayesian mixed effect quantile regression and find strongly varying covariate effects over the whole conditional distribution of credit conversion factors and especially between United States and Europe. If macroeconomic variables do not provide adequate downturn estimates, the model is enhanced by random effects. Results from European credit lines suggest that high conversion factors are driven by random effects rather than observable covariates. We further show that the impact of the economic surrounding highly depends on the level of utilization one year prior default, suggesting that credit lines with high drawdown potential are most affected by economic downturns and hence bear the highest risk in crisis periods. [ABSTRACT FROM AUTHOR]

This research explores the sensitivity of the returns of some selected European companies to changes in the explanatory factors proposed during the sample period between January 2000 and December 2019. We focus on listed companies in the tourism and services sector and estimate an extension of the Fama and French five-factor model (2015) by applying the quantile regression approach. Specifically, this study starts from the Fama and French risk factors and adds the nominal interest rates, a momentum and momentum reversal factors and a traded liquidity factor. For robustness, this research divides the whole sample period into three sub-periods: pre-crisis, crisis and post-crisis. In line with the previous literature, the explanatory power of this factor model shows a U-shape, which is compatible with the highest R 2 coefficients in the extreme quantiles, as well as in extreme stages of the economy, that is, in the bullish and bearish market states. [ABSTRACT FROM AUTHOR]

The high prevalence of hay fever in Europe has raised concerns about the implications of climate change-induced higher temperatures on pollen production. Our study focuses on downy birch pollen production across Europe by analyzing 456 catkins during 2019–2021 in 37 International Phenological Gardens (IPG) spanning a large geographic gradient. As IPGs rely on genetically identical plants, we were able to reduce the effects of genetic variability. We studied the potential association with masting behavior and three model specifications based on mean and quantile regression to assess the impact of meteorology (e.g., temperature and precipitation) and atmospheric gases (e.g., ozone (O 3) and carbon-dioxide (CO 2)) on pollen and catkin production, while controlling for tree age approximated by stem circumference. The results revealed a substantial geographic variability in mean pollen production, ranging from 1.9 to 2.5 million pollen grains per catkin. Regression analyses indicated that elevated average temperatures of the previous summer corresponded to increased pollen production, while higher O 3 levels led to a reduction. Additionally, catkins number was positively influenced by preceding summer's temperature and precipitation but negatively by O 3 levels. The investigation of quantile effects revealed that the impacts of mean temperature and O 3 levels from the previous summer varied throughout the conditional response distribution. We found that temperature predominantly affected trees characterized by a high pollen production. We therefore suggest that birches modulate their physiological processes to optimize pollen production under varying temperature regimes. In turn, O 3 levels negatively affected trees with pollen production levels exceeding the conditional median. We conclude that future temperature increase might exacerbate pollen production while other factors may modify (decrease in the case of O 3 and amplify for precipitation) this effect. Our comprehensive study sheds light on potential impacts of climate change on downy birch pollen production, which is crucial for birch reproduction and human health. [Display omitted] • Effects of climate change on birch pollen production across Europe are evaluated. • Pollen production tends to increase with average temperatures. • Pollen production tends to decrease with O 3 concentration levels. • Effects of temperatures and O 3 vary across response distribution. [ABSTRACT FROM AUTHOR]

Renewable energy production is necessary for digital society; it is also beneficial for labor market and sustainable development. This paper examines the impact of renewable energy production on unemployment rate by employing panel NARDL-PMG and robust asymmetric quantile regression for European countries from 1991 to 2019. The results reveal that renewable energy production significantly reduced unemployment in European countries in long run. The renewable energy production effect is found significant in the asymmetric model, specifically, in European countries; a positive change in renewable energy production has a negative significant impact on unemployment, and a negative change in renewable energy production has a positive significant impact on unemployment in long run. The GDP, investment, and technology innovation process are found to be triggered in labor market by reducing the unemployment rate in the long run. In addition, the asymmetric effects of renewable energy production on unemployment growth are robust in the different quantile regression. The findings suggest some insightful policy implications for government officials and policymakers. [ABSTRACT FROM AUTHOR]

Purpose: The authors investigate the implications of environmental, social and governance (ESG) practices of firms for the pricing of their credit default swaps (CDS). In doing so, the authors compare European and US firms and consider nonlinear and indirect effects. This complements the previous literature focusing on linear and direct effects using bond yields and credit ratings of US firms. Design/methodology/approach: For this purpose, the authors apply fixed effects regressions on a comprehensive panel data set of US and European firms. Further, nonlinear and indirect effects are investigated utilizing quantile regressions and a path analysis. Findings: The evidence indicates that higher ESG ratings mitigate credit risks of US and European firms from 2007 to 2019. The risk mitigation effect is U-shaped across ESG quantiles, which is consistent with opposing effects of growing stakeholder influence capacity and diminishing marginal returns on ESG investments. The authors further reveal a mediating indirect volatility channel that substantially amplifies the direct effect of ESG on credit risk. A one-standard-deviation improvement in ESG ratings is estimated to reduce CDS spreads of low, medium and high ESG firms by approximately 4%, 8% and 3%, respectively. Originality/value: This is the first study to examine whether credit markets reflect regional differences between Europe and the US with regard to the ESG-CDS-relationship. In addition, this paper contributes to the existing literature by investigating differences in the response of CDS spreads across ESG quantiles and to study potential indirect channels connecting ESG and CDS spreads using structural credit risk variables. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of this study is to describe the situation of COVID-19 in European countries and to identify important factors related to prevention and control. Methods: We obtained data from World Health Statistics 2020 and the Institute for Health Metrics and Evaluation (IHME). We calculated the Rt values of 51 countries in Europe under different prevention and control measures. We used lasso regression to screen factors associated with morbidity and mortality. For the selected variables, we used quantile regression to analyse the relevant influencing factors in countries with different levels of morbidity or mortality. Results: The government has a great influence on the change in Rt value through prevention and control measures. The most important factors for personal and group prevention and control are the mobility index, testing, the closure of educational facilities, restrictions on large-scale gatherings, and commercial restrictions. The number of ICU beds and doctors in medical resources are also key factors. Basic sanitation facilities, such as the proportion of safe drinking water, also have an impact on the COVID-19 epidemic. Conclusions: We described the current status of COVID-19 in European countries. Our findings demonstrated key factors in individual and group prevention measures. [ABSTRACT FROM AUTHOR]

We apply a multivariate mixed-data sampling (MIDAS) conditional quantile regression technique to understand the dairy commodity exposure of European dairy firms. Leveraging a theoretically sound hedonic dairy pricing framework, we show that our approach is able to identify both market and operational risk. Profit margins for butter and milk price are particularly important for operational performance. Additional tests are provided, including an application of MIDAS quantile on a period of amplified dairy market risk. Our approach thus allows dairy firms to gain new perspectives on the significant risks posed by the current structure of dairy production in Europe. [ABSTRACT FROM AUTHOR]

• A single IDF model valid for various return periods and durations is developed. • New scaling models of design rainfall curves are presented. • Adjusted rainfall event durations are considered in the context of scale invariance. • Parsimonious intensity–duration–frequency (IDF) structure is obtained. • Good fit to quantile predictions of extreme rainfall data for specified durations. This paper deals with intensity–duration–frequency (IDF) curves, which express the relationship between average rainfall intensity and event duration for various probabilities of non-exceedance (or return periods) for the design/analysis of hydraulic interventions and infrastructures in riverine and urban drainage contexts. New scaling models are proposed to develop a single IDF model valid for all durations, from below 1 h to 24 h. In these models, the scale invariance is applied to rainfall intensity to obtain a parsimonious IDF structure capable of defining a family of IDF curves at various return periods. The main novelty consists of the formulation of simple and multiple scale invariance based on adjusted design event durations. The parameterization is carried out in two phases: in the first phase, the adjustment size is searched for iteratively while the other parameters of the IDF structure are directly obtained in cascade; in the second phase, which enables considering different reliability levels for extreme rainfall data as a function of sample length at different durations, parameter refinement is carried out by means of a local optimization algorithm. The second step accommodates data samples of different extension as a function of available data at different durations. The application to four case studies at various latitudes in Europe, namely Helsinborg (Sweden), Frauenwald (Germany), Pavia and Erice (Italy), proves the IDF structure to fit well the quantile predictions of extreme rainfall data for specified durations below and above one hour. [ABSTRACT FROM AUTHOR]

This paper analyses the sensitivity of the most relevant European financial institutions' returns to changes in selected risk factors between October 2003 and December 2018. In concrete, this research estimates, using the quantile regression approach, extensions of the Fama and French five-factor model (2015), adding nominal interest rates, the Carhart (1997) risk factor for momentum and momentum reversal and the Pastor and Stambaugh (2003) traded liquidity factor. To consider the economic cycle, a robustness check splits the whole sample period into three sub-sample periods (pre-crisis, crisis and post-crisis). As expected, this extension of the Fama and French model has the highest explanatory power in the highest and the lowest quantiles, showing a U-shaped pattern. In addition, our proposed model reaches a better explanation of the changes in European companies' returns in extreme stages of the economy. Therefore, in general, the sensitivity of stock returns of the largest European financial institutions to movements in risk factors tends to be more marked in bullish and bearish scenarios, that is, in extreme market conditions. These results are partially replicated for a number of selected small and mid-cap European banks. [ABSTRACT FROM AUTHOR]

Aim: A fundamental question in macroecology centres around understanding the relationship between species' local abundance and their distribution in geographical and climatic space (i.e. the multi‐dimensional climatic space or climatic niche). Here, we tested three macroecological hypotheses that link local abundance to the following range properties: (a) the abundance–range size relationship, (b) the abundance–range centre relationship and (c) the abundance–suitability relationship. Location: Europe. Taxon: Vascular plants. Methods: Distribution range maps were extracted from the Chorological Database Halle to derive information on the range and niche sizes of 517 European vascular plant species. To estimate local abundance, we assessed samples from 744,513 vegetation plots in the European Vegetation Archive, where local species' abundance is available as plant cover per plot. We then calculated the 'centrality', that is, the distance between the location of the abundance observation and each species' range centre in geographical and climatic space. The climatic suitability of plot locations was estimated using coarse‐grain species distribution models (SDMs). The relationships between centrality or climatic suitability with abundance was tested using linear models and quantile regression. We summarized the overall trend across species' regression slopes from linear models and quantile regression using a meta‐analytical approach. Results: We did not detect any positive relationships between a species' mean local abundance and the size of its geographical range or climatic niche. Contrasting yet significant correlations were detected between abundance and centrality or climatic suitability among species. Main conclusions: Our results do not provide unequivocal support for any of the relationships tested, demonstrating that determining properties of species' distributions at large grains and extents might be of limited use for predicting local abundance, including current SDM approaches. We conclude that environmental factors influencing individual performance and local abundance are likely to differ from those factors driving plant species' distribution at coarse resolution and broad geographical extents. [ABSTRACT FROM AUTHOR]

The aim of the paper is to assess the effect of discretionary accruals on firm growth while controlling for firm characteristics and macroeconomic environment. Employing a large sample of 1.105 young and high-growth firms (gazelles) from 15 emerging European countries over the period 2006-2014, it has been found that the discretionary accruals negatively influence firm growth. The empirical results suggest that discretionary accruals are used as earnings management tools and this practice is more used over the high-growth period (2006-2009), with negative effects on future performance. Furthermore, the results of the quantile regression employed in the whole period suggest that the earnings management practices have a negative effect on firm growth. The results prove to be robust for different estimation approaches and different sub-samples of gazelles. The findings provide empirical evidence for the need for more detailed information provided by firms on the origin of the accruals, as well as for the use in the performance analysis of some indicators that eliminate the influence of accruals, such as cash flow based ratios. [ABSTRACT FROM AUTHOR]

In this paper we investigate gender wage disparities in 25 EU countries before and after the crisis, focusing on the role employment protection legislation played in shaping the gap across the wage distribution. Results of quantile regressions reveal a remarkable cross-country diversity in the size of the gap and confirm the widespread existence of glass-ceiling effects. Stricter rules for temporary contracts mitigate the gender gap, especially at the top of the distribution; stronger protection for permanent workers is found to increase the gap at the bottom of the distribution and to decrease it at the middle and at the top. [ABSTRACT FROM AUTHOR]

Impact models are a major source of information for quantifying the consequences of future climate change for humans and the environment. To provide plausible outputs, these models require unbiased high resolution meteorological data as input for atmospheric conditions. State of the art regional climate models (RCMs) often fail to provide such data, since they can exhibit large systematic biases. Therefore, bias correction methods (BCMs) have become a common tool in climate impact studies. Bias correction, however, comes with strong assumptions and limitations, often resulting from the fact that most BCMs are unable to appropriately calibrate a time dependent and conditional transfer function. To address this problem, we introduce here regression quantile mapping (RQM), a bias correction approach based on (linear) regression models which allow to design transfer functions based on expert knowledge. The new RQM algorithm is described in full detail in its basic (linear model) version and applied to RCM generated precipitation data for entire Europe. Based on the latter example, we provide a thorough comparison with another established BCM, quantile delta mapping (QDM) regarding the seasonal characteristics of precipitation sums. Our results demonstrate that RQM already achieves good results when a simple linear model is used. The relationship between precipitation and temperature was properly evaluated by RQM and representation of seasonal variations and key characteristics of precipitation were improved for most seasons. Systematic biases where reduced significantly during this process. Particular improvements in comparison with QDM are found regarding the shape and width of the distribution of bias corrected model precipitation. Furthermore, the representation of precipitation extremes within the data was largely improved when RQM was used instead of QDM. [ABSTRACT FROM AUTHOR]

Introduction: Despite the improvements in European health systems, a large number of premature deaths are attributable to treatable mortality. Men make up the majority of these deaths, with a significant gap existing between women and men's treatable mortality rate in the EU., Aim: This study aims to identify the healthcare-related factors, including health expenditures, human and physical resources, and hospital services use associated with treatable mortality in women and men across European countries during the period 2011-2019., Methods: We use Eurostat data for 28 EU countries in the period 2011-2019. We estimate a panel data linear regression with country fixed effects and quantile linear regression for men and women., Results: The results found (i) differences in drivers for male and female treatable mortality, but common drivers hold the same direction for both sexes; (ii) favorable drivers are GDP per capita , health expenditures, number of physicians per capita , and (only for men) the average length of a hospital stay, (iii) unfavorable drivers are nurses and beds per capita , although nurses are not significant for explaining female mortality., Conclusion: Policy recommendations may arise that involve an improvement in hospital bed management and the design of more specific policies aimed at healthcare professionals., Competing Interests: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Tavares.)

Using a macro panel of 31 European countries, this study shows that the application of quantile regression (QR) procedures to the estimation of poverty risk reveals that poverty determinants and cross-country differences in poverty levels are more reliable than those emerging from conditional mean estimations. The extent and significance of interquartile differences of estimated coefficients suggest that economic growth, income distribution, public expenditure, investment, education, and the labor's share of income – aproxy for functional income distribution or social antagonism – have strong but differentiated effects on poverty reduction. Low-institutional quality exemplified by the high public-sector-corruption perception has a significant concomitant adverse effect on poverty and interacts with economic cofactors in determining interquartile differences of estimated coefficients. Results show that the implementation of a common European Union policy against poverty should consider cross-country interquartile differences and avoid a one-size-fits-all uniform philosophy. [ABSTRACT FROM AUTHOR]

Considering the recent extreme precipitation in southeast Europe, it has become necessity to investigate the impact of climate change on extreme precipitation. The aim of this study was to determine the change in precipitation quantiles with longer return periods under changing climate conditions. The study was conducted using the daily records gathered at 11 precipitation stations within the Lim River Basin, Serbia. The simulated precipitation datasets were collected from three regional climate models for the baseline period (1971–2000), as well as the future period (2006–2055) under the 2.6, 4.5 and 8.5 representative concentration pathways. The raw precipitation data from the climate models were transformed by employing four bias correction methods. Using the bias-corrected precipitation, an ensemble of annual maximum daily precipitation was developed. A weighted ensemble approach was applied to estimate the weights of each ensemble member favorizing the members whose quantiles were closer to observed measurements. The mixed general extreme value distribution was used to derive the projected quantiles with 100, 50, 25, 10, five and two year return periods based on the estimated quantiles and the normalized weights of all ensemble members. An overall increase of 69% and 56% for the 100 and 50 year return periods, respectively, can be expected within the northern part of the basin. Similarly, an overall increase of 50–57% and 39–42% for the 100 and 50 year return periods, respectively, may be expected for the central and southern parts of the Lim River Basin. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1007/s10666-023-09877-2. B Correction to: Environmental Modeling & Assessment b https://doi.org/10.1007/s10666-023-09877-2 The original version of the article unfortunately contained an error. [Extracted from the article]

This research estimates the impact of climate on European agriculture using a continental scale Ricardian analysis. Climate, soil, geography and regional socio-economic variables are matched with farm level data from 41,030 farms across Western Europe. We demonstrate that a median quantile regression outperforms OLS given farm level data. The results suggest that European farms are slightly more sensitive to warming than American farms with impacts from $$+$$ 5 to $$-$$ 32 % by 2100 depending on the climate scenario. Farms in Southern Europe are predicted to be particularly sensitive, suffering losses of $$-$$ 5 to $$-$$ 9 % per degree Celsius. [ABSTRACT FROM AUTHOR]

By analysing 796 companies' data from 21 European countries, this research uncovered the nexus between institutional quality (IQ) and corporate sustainable performance (CSP). The relationship was theoretically examined with the lens of institutional theory and then empirically tested. The findings show that IQ has a positive and significant impact in safeguarding CSP, and firms' characteristics play an essential preamble in this regard. We additionally found the heterogeneous impact of IQ on CSP. To come to a conclusion, we have applied random effect, two-step system GMM and quantile regression models. Our findings are consistent and empirically robust; therefore, the study disseminates key messages to policymakers and practitioners about the role of IQ in safeguarding CSP. [ABSTRACT FROM AUTHOR]

This article sheds light on the differences in the mechanisms generating intergenerational inequality in the four largest Euro Area economies (Spain, Italy, Germany and France) looking at the association between parental background and sons' earnings along the sons' distribution. We find that in all countries returns to parental background increase along the sons' earnings distribution and the probability of ending up in high deciles is significantly correlated with parental background. However, although these findings lend support to the existence of a common mechanism, substantial differences in returns' steepness question the one-pattern-fits-all story. [ABSTRACT FROM AUTHOR]

Purpose: Different health state utility (HSU) instruments produce different utilities for the same individuals, thereby compromising the intended comparability of economic evaluations of health care interventions. When developing crosswalks, previous studies have indicated nonlinear relationships. This paper inquires into the degree of nonlinearity across the four most widely used HSU-instruments and proposes exchange rates that differ depending on the severity levels of the health state utility scale.Methods: Overall, 7933 respondents from six countries, 1760 in a non-diagnosed healthy group and 6173 in seven disease groups, reported their health states using four different instruments: EQ-5D-5L, SF-6D, HUI-3 and 15D. Quantile regressions investigate the degree of nonlinear relationships between these instruments. To compare the instruments across different disease severities, we split the health state utility scale into utility intervals with 0.2 successive decrements in utility starting from perfect health at 1.00. Exchange rates (ERs) are calculated as the mean utility difference between two utility intervals on one HSU-instrument divided by the difference in mean utility on another HSU-instrument.Results: Quantile regressions reveal significant nonlinear relationships across all four HSU-instruments. The degrees of nonlinearities differ, with a maximum degree of difference in the coefficients along the health state utility scale of 3.34 when SF-6D is regressed on EQ-5D. At the lower end of the health state utility scale, the exchange rate from SF-6D to EQ-5D is 2.11, whilst at the upper end it is 0.38.Conclusion: Comparisons at different utility levels illustrate the fallacy of using linear functions as crosswalks between HSU-instruments. The existence of nonlinear relationships between different HSU-instruments suggests that level-specific exchange rates should be used when converting a change in utility on the instrument used, onto a corresponding utility change had another instrument been used. Accounting for nonlinearities will increase the validity of the comparison for decision makers when faced with a choice between interventions whose calculations of QALY gains have been based on different HSU-instruments. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate, from a generational perspective, the effect of human capital on individual earnings and earnings differences in Germany, France and Italy, three developed countries in Western Europe with similarconservativewelfare regimes but with important differences in their education systems. Income inequalitiesbetweenandwithineducation levels are explored using a two-stage probit model with quantile regressions in the second stage. More precisely, drawing upon 2005 EU-SILC data, returns on schooling and experience are estimated separately for employees and self-employed full-time workers by means of Mincerian earnings equations with sample selection; the sample selection correction accounts for the potential individual self-selection into the two labour force types. Although some determinants appear to be relatively similar across countries, state-specific differentials are drawn in light of the institutional features of each national context. The study reveals how each dimension of human capital differently affects individuals’ earnings and earnings inequality and, most of all, how their impacts differ along the conditional earnings distribution and across countries. In the comparative perspective, the country's leading position in terms of the highest rewards on education also depends on which earnings distribution (employee vs. self-employed) is analysed. [ABSTRACT FROM PUBLISHER]

This paper investigates the presence of gregarious behavior of investors for the European emerging stock markets: Romania, Bulgaria and Croatia at industry level using an adjusted CSSD method, in order to correct the multicollinearity and to improve the power of the model. The herding behavior is associated with the market participants' tendency to mimicry the strategies of others investors, thus disregarding the information they hold. Using a quantile regression model, we highlight the existence of herding behavior both for lower and upper quantiles. Furthermore, the period when the investors exhibit herding behavior is various: for Croatia the herding occurs in the pre-crisis period, in the case of Bulgaria, it is prevalent during crisis period, and finally for Romania it was found to be predominant in the post-crisis period. [ABSTRACT FROM AUTHOR]

This paper estimates cost efficiency in the banking industry of 11 Central and Eastern European (CEE) countries over the period 1998–2005 using a quantile regression analysis. Our purpose is to investigate for the first time whether cost efficiency in CEE banks differs across quantiles of the conditional distribution. We employ stochastic frontier analysis across quantiles using the Distribution-Free Approach. The reported evidence demonstrates lower efficiency scores for higher conditional distributions. The paper goes further into a second-stage analysis to investigate how risk, measured by non-performing loans and loans loss provisions, affects bank efficiency across quantiles. This second-stage analysis finds that risk asserts a negative impact on cost efficiency, especially in high-order quantiles. Finally, the paper investigates the relationship between bank-specific ‘z’ variables, such as structural reforms, bank concentration and profitability, and cost efficiency across quantiles. [ABSTRACT FROM AUTHOR]

This article provides new insights into the dependence of firm growth on age along the entire distribution of growth rates, and conditional on survival. Using data from the European firms in a global economy survey, and adopting a quantile regression approach, we uncover evidence for a sample of French, Italian and Spanish manufacturing firms with more than ten employees in the period from 2001 to 2008. We find that: (1) young firms grow faster than old firms, especially in the highest growth quantiles; (2) young firms face the same probability of declining as their older counterparts; (3) results are robust to the inclusion of other firms' characteristics such as labor productivity, capital intensity and the financial structure; (4) high growth is associated with younger chief executive officers and other attributes that capture the attitude of the firm toward growth and change. The effect of age on firm growth is rather similar across countries. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the relationship between mood and air travel choices, considering the role of travel significance and the influence that COVID-19 may have on younger generations' choices. Using a mixed-methods sequential exploratory design, a sample of 1,111 Italian respondents, belonging to younger generations is investigated. The data are analysed using a quantile regression with group effects considering attitudes towards COVID-19. The study demonstrates that there is a positive and significant relationship between mood and the number of journeys by air to destinations outside Europe, highlighting the positive moderating effect of the air travel experience and the negative moderating effect of COVID-19. This may have important implications for air transport managers interested in luring younger people to fly in the post-COVID19 era. • Younger generations regard travelling an important aspect of their life. • The mood of travelling varies across young people. • Mood is influenced by the number of undertaken long-haul trips. • The reaction to COVID-19 influences the relationship between mood and air transport. [ABSTRACT FROM AUTHOR]

This paper uses a sample of private sector male workers from the European Community Household Panel to examine the wage effects of educational mismatches across segments of the earnings distribution in 12 countries. We consider two types of mismatch, overqualification and skills mismatches. By differentiating between quantiles, we discriminate between groups of workers with different unobservable earnings conditions. We find that the detrimental effects of skill mismatches on wages are larger than those of overqualification in most segments of the earnings distribution. Moreover, we find that the pay penalty of educational mismatch tends to be higher among workers with higher unconditional wages. This finding suggests that the mismatch phenomenon entails wage losses over and above those attributable to unobservable earnings determinants, including ability and skills possessed by workers. [ABSTRACT FROM AUTHOR]

This paper looks at firm-level differences in R&D intensity and sales from product innovations. R&D intensity and innovative sales are explained by a model using harmonised firm-level data from the Third Community Innovation Survey for three European countries: Belgium, Germany and Spain. For each country, the average estimates suggest that incoming knowledge spillovers, research cooperation, appropriability and human capital all exercise a positive influence on R&D intensity and, through this, on innovative sales. Quantile regressions indicate that, although there are differences between countries, the joint relative impact of incoming knowledge spillovers and research cooperation tends to increase quantile-wise in relation to that of appropriability. This suggests that strong innovators have a more open innovation process. [ABSTRACT FROM AUTHOR]

A safe, clean water supply is critical for sustaining many important ecosystem services provided by freshwaters. The development of cyanobacterial blooms in lakes and reservoirs has a major impact on the provision of these services, particularly limiting their use for recreation and water supply for drinking and spray irrigation. Nutrient enrichment is thought to be the most important pressure responsible for the widespread increase in cyanobacterial blooms in recent decades. Quantifying how nutrients limit cyanobacterial abundance in lakes is, therefore, a key need for setting robust targets for the management of freshwaters., Using a data set from over 800 European lakes, we highlight the use of quantile regression modelling for understanding the maximum potential capacity of cyanobacteria in relation to total phosphorus ( TP) and the use of a range of quantile responses, alongside World Health Organisation ( WHO) health alert thresholds for recreational waters, for setting robust phosphorus targets for lake management in relation to water use., The analysis shows that cyanobacteria exhibit a nonlinear response to phosphorus with the sharpest increase in cyanobacterial abundance occurring in the TP range from about 20 μg L−1 up to about 100 μg L−1., The likelihood of exceeding the World Health Organisation ( WHO) 'low health alert' threshold increases from about 5% exceedance at 16 μg L−1 to 40% exceedance at 54 μg L−1. About 50% of the studied lakes remain below this WHO health alert threshold, irrespective of high summer TP concentrations, highlighting the importance of other factors affecting cyanobacteria population growth and loss processes, such as high flushing rate., Synthesis and applications. Developing a more quantitative understanding of the effect of nutrients on cyanobacterial abundance in freshwater lakes provides important knowledge for restoring and sustaining a safe, clean water supply for multiple uses. Our models can be used to set nutrient targets to sustain recreational services and provide different levels of precaution that can be chosen dependent on the importance of the service provision. [ABSTRACT FROM AUTHOR]

Abstract: It has been widely stated that pressures acting at large spatial scales influence local habitat conditions and might limit the effects of local restoration measures. However, only a few empirical studies have used statistical methods that have explicitly been developed to investigate such wedge-shaped relationships. The objectives of the present study were (i) to identify pressures acting as limiting factors and to investigate the mitigating effects of local restoration measures in three datasets from European rivers, (ii) to derive thresholds for the ecological status of invertebrates, and (iii) to compare results derived from two statistical approaches, one using aggregated response variables like biological metrics (quantile regression trees), another using taxon-specific responses to derive separate community thresholds for the negative response of sensitive and the positive response of tolerant taxa (Threshold Indicator Taxa Analysis, TITAN). The results indicated that wedge-shaped relationships, typically resulting from limiting factors, are common in datasets from Central European rivers. There was empirical evidence for limiting effects of water pollution and catchment land use and an indication of a mitigating effect of hydromorphological restoration measures. The results emphasize the need to consider such large-scale pressures in river management and restoration because they potentially constrain the effects of local restoration measures. The thresholds derived for the aggregated response variables (metrics) and the community thresholds for sensitive taxa were in good agreement with values reported in the literature but differed markedly depending on the statistical method used. A possible reason is the different focuses of the methods on (i) the threshold for an aggregated response variable (metric), which includes the negative and positive response, and hence, reflects ecosystem functioning, and (ii) the community threshold of sensitive taxa based on taxon-specific negative responses, which is possibly best suited for species conservation issues. However, this interpretation requires further analysis since the results of the two methods showed no consistent differences. [Copyright &y& Elsevier]

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The paper re-examines the issue of the robustness of the weekday effect. Specifically, by utilizing a quantile regression approach, the homogeneity of observed day-of-the-week anomalies is monitored and tested over different parts of the conditional return distribution. The day-of-the-week effects are measured for conditional returns as well as for conditional volatilities. The model applied accounts for asymmetry in first-order autocorrelation in both moments. The weekday patterns in the returns on the European market index and 18 European country indexes are analyzed for the time period from January 2000 through December 2006. Generally, the sign of the estimated weekday effects in both the conditional mean and volatility seems to be very robust over the return distribution. However, about one half of the country-specific indexes exhibit significant variation or asymmetry in the day-of-the-week coefficients across the quantiles of the conditional return distribution. Only in a few cases, the significant day-of-the-week effect is clearly driven by extreme events. [ABSTRACT FROM AUTHOR]

Abstract: The paper presents a methodology for estimating high quantiles of distributions of daily temperature in a non-stationary context, based on peaks-over-threshold analysis with a time-dependent threshold expressed in terms of regression quantiles. The extreme value models are applied to estimate 20-yr return values of maximum daily temperature over Europe in transient global climate model (GCM) simulations for the 21st century. A comparison of scenarios of changes in the 20-yr return temperatures based on the non-stationary peaks-over-threshold models with conventional stationary models is performed. It is demonstrated that the application of the stationary extreme value models in temperature data from GCM scenarios yields results that may be to a large extent biased, while the non-stationary models lead to spatial patterns that are robust and enable one to detect areas where the projected warming in the tail of the distribution of daily temperatures is largest. The method also allows splitting the projected warming of extremely high quantiles into two parts that reflect change in the location and scale of the distribution of extremes, respectively. Spatial patterns of the two components differ significantly in the examined climate change projections over Europe. [Copyright &y& Elsevier]

• Analysis of trends in adolescent alcohol use with quantile regression models. • Changes happened collectively in 15, and polarised in 11 European countries. • Consumption levels are diverging in 18 of 26 European countries. • Diverging trends indicate less beneficial change in heavy compared with light users. • Policy measures need to target the whole population as well as specific risk groups. The present paper extends the scope of testing Skog's theory on the 'collectivity of drinking culture' to adolescent alcohol use in 26 European countries. The aim was to 1) examine whether changes in adolescent alcohol use are consistent across different consumption levels, and 2) explore whether trends in heavy and light drinkers diverged or converged. Data came from six waves of the cross-sectional European School Survey Project on Alcohol and other Drugs (ESPAD) between 1999 and 2019. The sample consisted of n = 452,935 students aged 15–16 years. Trends in alcohol volume across consumption levels including abstainers were estimated by quantile regression models (50th, 80th, 90th and 95th percentile). Countries were classified according to trends showing (soft/hard) collectivity or (soft/hard) polarisation. Trends in heavy drinkers were compared with the population trend. Trends in alcohol consumption at different levels across 26 European countries in the period 1999–2019 were not homogeneous. Collective changes were found in 15 (14 soft/1 hard), and polarised trends in 11 countries (5 soft/6 hard). Collectivity was generally associated with a declining trend. In 18 countries, trends in heavy and light drinkers diverged. Accepting some variation in the strength of changes across consumption levels, changes in many European countries occurred in the same direction. Yet, diverging trends at different consumption levels in most countries indicate a less beneficial change in heavy compared with light drinkers, implying that in addition to universal population-level strategies, intervention strategies targeting specific risk groups are needed to prevent alcohol-related harm. [ABSTRACT FROM AUTHOR]

[Display omitted] • The impact of temperature change on firm profitability is analyzed. • A quantile regression approach is employed on firms active in the energy and gas sector. • An increase in the annual temperature has a positive impact on firm profitability. • This positive effect varies at different quantiles of the performance distribution. • Market concentration and energy prices have a significant influence on firm profitability. Although temperature change is affecting economic activity, there are a few empirical studies on how it influences firm performance. Using panel data of 147 European listed firms active in the energy and gas sectors over the period 2009–2016, this study aims to analyze the impact of temperature change on firm profitability while controlling for firm-specific and energy market-related factors. The results of the quantile regression approach show that an increase in the annual temperature has a positive impact on firm profitability. However, this impact varies at different quantiles of the profitability distribution. A 1℃ degree increase in temperature is related to a 1.30% increase in operating profitability for the most profitable firms (Q90). However, the magnitude of this impact is lower for less profitable firms (Q10 and Q25). The empirical results revealed that cash flows, market opportunities, leverage, firm size, net asset turnover, as well as market concentration and energy prices, have a significant influence on firm profitability in the energy and gas sectors. These findings appear to be robust to several control variables and robustness tests. The study provides empirical evidence on the impact of climate change on the performance of firms active in climate-sensitive sectors (such as energy and gas sectors). The findings of this study are particularly helpful for portfolio risk managers, energy traders, and policymakers. [ABSTRACT FROM AUTHOR]

We create cross-quantilogram networks capturing the dependence between stock market returns of 205 financial institutions in Europe and across a large range of quantiles. Based on network density, centrality and centralization, we find that financial institutions in Europe are strongly interconnected across all quantiles, particularly during tranquil periods. These results suggest that financial institutions in Europe are susceptible to spillover, contagion and increased systemic risk. We also find an asymmetric effect: connectedness during crisis periods is higher than that during bullish periods. The most interconnected financial institutions are found to be insurance companies in Switzerland. Relying on an exponential random graph modeling (ERGM) approach, we find that across all quantiles, the connectedness is larger between (i) financial institutions in the same country, (ii) insurance companies, and (iii) financial institutions that operate in countries that adopted the common currency. • We study the financial connectedness of 205 financial institutions in Europe. • Statistically validated networks are created using cross-quantilogram analysis. • European financial institutions are strongly interconnected during tranquil periods. • Interconnectedness is asymmetric: Higher during crisis periods. • ERGM analysis identifies several drivers of increased interconnectedness. [ABSTRACT FROM AUTHOR]

• Phytobenthos in lowland lakes in Romania does not demonstrate a strong response to phosphorus. • Assemblage composition is, instead, determined by biochemical oxygen demand and conductivity. • A new metric to evaluate ecological status using phytobenthos in these lakes is described. • Expected values of this metric are derived from a quantile regression of the index against conductivity. • As conductivity is susceptible to climate change, 2010 values are used as benchmarks when calculating expected index values. In contrast to diatom assemblages in lakes in most other parts of Europe, those in lowland lakes in Romania appear to be determined primarily by biochemical oxygen demand (BOD) and conductivity rather than by nutrients. This has confounded the development of a Water Framework Directive-compatible phytobenthos assessment system for Romanian lakes and led, instead, to the development of a new metric, the Romanian Diatom Index (RDI), which captures these gradients. The primary anthropogenic stressor is assumed to be BOD whilst conductivity is a product of background geology and climate. The RDI is strongly correlated with BOD, and ecological quality ratios (EQRs) are computed by dividing the observed RDI by an expected value, determined from the 90th percentile of the relationship between RDI and conductivity. This equates to the "best available" RDI at any point on the conductivity gradient and, in the absence of true "reference sites", has been assumed to represent the boundary between high and good status. The boundary between good and moderate status has been set at the point where the sum of valves of taxa tolerant to elevated BOD exceeds the sum of valves of taxa that are sensitive to elevated BOD. The position of this boundary has been further validated by the use of a Threshold Indicator Species Analysis (TITAN). In view of the susceptibility of conductivity to climate warming, 2010 values of conductivity have been used to ensure a stable benchmark against which future changes can be measured. This study highlights the challenges involved in performing reliable ecological assessments in situations that are, by the standards of much of Europe, atypical. [ABSTRACT FROM AUTHOR]