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This study examined the quadratic role of renewable energy and economic growth on environment quality in Asia's five most populous countries: China, India, Indonesia, Pakistan, and Bangladesh. Previous literature has scarcely addressed these economies and ignores the quadratic role of GDP per capita (GDPPC) and renewable energy (REN) together in a single study. Therefore, using STIRPAT model, we first added the quadratic term of GDPPC and then REN. In both cases, a quantile regression technique is utilised to identify the inclusive relationship between CO2 emissions and determining factors, considering different quantiles (0.25, 0.50, 0.75, 0.90, and 0.95) of CO2 emissions. The findings show that during the annual sample period of 1983–2019, urbanisation, GDPPC, non‐renewable energy, and REN all have an impact on CO2 emissions. Urbanisation and REN have nominal effects, with a 1% change in these variables leading to a 0.19% and 0.05% change in CO2 emissions, respectively. Non‐renewable energy and GDPPC are found to be main sources of CO2 emissions in the region. GDPPC is positively associated with CO2 emissions across all quantiles, but higher quantiles show a stronger correlation (i.e., GDPPC coefficients vary from 0.26 to 0.66). In addition, the results also revealed that the square term of GDPPC and REN significantly reduces CO2 emissions. This implies that our results support the environmental Kuznets curve (EKC) hypothesis; an inverted U‐shaped is established for both GDPPC and REN. These results encourage policy makers to adopt renewable energy that is both growth and environment friendly. [ABSTRACT FROM AUTHOR]

Summary: Quantile regression methods are increasingly used to forecast tail risks and uncertainties in macroeconomic outcomes. This paper reconsiders how to construct predictive densities from quantile regressions. We compare a popular two‐step approach that fits a specific parametric density to the quantile forecasts with a nonparametric alternative that lets the "data speak." Simulation evidence and an application revisiting GDP growth uncertainties in the United States demonstrate the flexibility of the nonparametric approach when constructing density forecasts from both frequentist and Bayesian quantile regressions. They identify its ability to unmask deviations from symmetrical and unimodal densities. The dominant macroeconomic narrative becomes one of the evolution, over the business cycle, of multimodalities rather than asymmetries in the predictive distribution of GDP growth when conditioned on financial conditions. [ABSTRACT FROM AUTHOR]

This article analyzes the effects of sanctions for unemployed recipients of the social assistance benefit in Germany. I conduct an analysis using administrative data from 2012 to 2018, applying a dynamic entropy balancing approach. In contrast to most previous analyses of benefit sanction effects, I analyse outcomes over a longer period and assess effects on various dimensions of employment quality, including education (mis)match. The results show, in line with previous research, that benefit sanctions increase the employment probability in the first months after treatment. In the long run, the employment probability and employment quality of sanctioned benefit recipients are lower than those for the comparison group of non-sanctioned benefit recipients, indicating long-lasting negative effects. The negative consequences of benefit sanctions for employment quality are hence not temporary, but persistent. [ABSTRACT FROM AUTHOR]

AbstractThis study seeks to find out whether climate finance (CF) geared toward 35 Sub Saharan Africa (SSA) countries is assisting to achieve food security in the continent. To achieve this objective, we adopted FAO’s classification of food security of 4 main dimensions: food availability, access, stability and utilization and use principal component analysis (PCA) to generate food security indexes corresponding to the different dimensions of food security. The data was analyzed using system generalized methods of moments (GMM) whereas panel quantile regression (PQR) was employed as a sensitivity analysis. Our findings show that climate finance is more useful in securing food availability but fails to enhance food access, stability and utilization. Further analysis shows that other factors such as foreign direct investment and government readiness have more impact in enhancing the different dimensions of food security whilst rural population, agricultural spending, agricultural land and capacity have more adverse effects on food security. Relevant policy implications based on our analysis are discussed.

The study examines the nexus between global energy commodity and its constituent across market conditions using the quantile regression approaches. We found that the positive effect of global energy commodity on its constituents was stronger relative to the feedback effect from the constituents. It is pertinent to hedge against fluctuations in the energy commodities using the global energy commodity as an appropriate hedged asset with the required hedging instrument. [ABSTRACT FROM AUTHOR]

This article employs quantile regressions to investigate the link between oil prices, gold prices, and stock market returns in five African oil-exporting nations: Nigeria, Ghana, Egypt, Algeria, and Tunisia. The analysis utilises daily data spanning from January 1, 2017, through September 30, 2021. Before the onset of COVID-19, oil played a pivotal role as a hedge in Tunisia, Egypt, Algeria, and Ghana, providing stability in both normal and bullish market conditions. Furthermore, it functioned as a diversifier in Egypt and Ghana during bearish market phases. However, as the pandemic unfolded, oil took on the characteristics of a safe haven in Egypt, Ghana, Nigeria, Algeria, and Tunisia, particularly notable during bearish and normal market conditions. Gold, prior to the pandemic, served as a hedge in Egypt, Ghana, Nigeria, and Tunisia, while also acting as a diversifier across both bearish and bullish market conditions in these economies. Conversely, during the pandemic, gold predominantly functioned as a diversifier in most oil-exporting African economies, with significant hedge properties observed specifically in Algeria and Ghana. The practical implications of these findings are significant for various stakeholders, including oil exploration and production firms, businesses in the transport and hospitality sectors, policymakers, and investors with stocks sensitive to oil and gold prices.

This article aimed to analyze the behavior of the northeastern municipal economic dynamics explained in the Gross Domestic Product (GDP) in relation to the volume of the Bolsa Família Program (PBF) destined for each entity, the proportion obtained from the Votes by the Mayor Elected (VPE) in the face of the set of voters participating in the election on the spot and the Mayor-Elect Party Coalition (CPPE) established or not with the state governor, based on per capita variables, in the period of 2004, 2008, 2012 and 2016. Methodologically, it was used to measurement of research results the quantile regression model for panel data. The results showed that GDP responded positively to PBF and negatively in most countries. municipalities to the VPE and CPPE did not bring favorable impacts on the northeastern municipal economy. [ABSTRACT FROM AUTHOR]

This study seeks to find out whether climate finance (CF) geared toward 35 Sub Saharan Africa (SSA) countries is assisting to achieve food security in the continent. To achieve this objective, we adopted FAO's classification of food security of 4 main dimensions: food availability, access, stability and utilization and use principal component analysis (PCA) to generate food security indexes corresponding to the different dimensions of food security. The data was analyzed using system generalized methods of moments (GMM) whereas panel quantile regression (PQR) was employed as a sensitivity analysis. Our findings show that climate finance is more useful in securing food availability but fails to enhance food access, stability and utilization. Further analysis shows that other factors such as foreign direct investment and government readiness have more impact in enhancing the different dimensions of food security whilst rural population, agricultural spending, agricultural land and capacity have more adverse effects on food security. Relevant policy implications based on our analysis are discussed. Public Interest Statement: Global warming is a significant human concern. Despite minimal contributions to climate change, African countries suffer disproportionately due to limited resources for mitigation and adaptation to climate change. Industrialized economies, major contributors to climate change, have committed climate funds to aid less developed nations. Our study assesses the impact of climate finance on ensuring food security in 35 Sub-Saharan African countries, crucial given the region's vulnerability to food scarcity due to climate change. Results reveal that while climate finance may promote food availability, it falls short in enhancing access, stability, and utilization. Other factors like government readiness, agricultural spending and foreign direct investment are found to be contribute to different dimensions of food security. Policy implications arising from our findings are discussed. [ABSTRACT FROM AUTHOR]

We implement the VIX methodology on intraday data of a large set of individual equity options. We thereby consider approaches based on monthly option contracts, weekly option contracts, and a cubic spline interpolation approach. Relying on 1 min, 10 min, and 60 min model-free implied volatility measures, we empirically examine the individual equity return–volatility relationship on the intraday level using quantile regressions. The results confirm a negative contemporaneous link between stock returns and volatility, which is more pronounced in the tails of the distributions. Our findings hint at behavioral biases causing the asymmetric return–volatility link rather than the leverage and volatility-feedback effects. [ABSTRACT FROM AUTHOR]

The heterogeneity of the national socio-economic space implies the assessment of regional peculiarities of innovation activity responses to localized sets of various resources that contribute to its activation. One of the most important elements in the composition of these sets of resources is the institutional conditions in the respective territory, the diversity of which at a given degree of technological and economic development can bear different results. These assumptions served as the basis for the present study, the purpose of which is to substantiate the manifestation of various institutional effects arising in Russian regions and to assess their impact on innovative development. In this study, the authors understand institutional factors as scientific and educational potential, the level of bureaucracy as one of the consequences of the local specificity of managerial impacts, the level of criminality, and entrepreneurial activity. The subject of the study is institutional effects resulting from the action of institutional factors affecting the innovative development of Russian regions. The aim is to assess the influence of institutional effects, i.e. scientific and educational environment, entrepreneurial, criminogenic, and bureaucratic, on the level of innovative development of regions. Panel data on 83 subjects of the Russian Federation for the period between the years 2000 and 2020 were used as the information basis. The peculiarity of the study is the use of the quantile regression method. The results of the study reveal positive influence of the effects of scientific and educational environment, and entrepreneurship and negative influence of the bureaucratic effect for all groups of regions. The inverse U-shaped relation between the criminogenic effect and innovation activity was confirmed for 80% of regions. It was found that the quality of institutions and the development of small entrepreneurship are more significant for regions with a low level of innovation activity than for regions that are innovation leaders

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]

AbstractThe purpose of our study is to examine the Fishery-based Environmental Kuznets Curve (EKC) for a sample of 48 African countries between 1970–2019. We estimate cubic EKC-type models using quantile regression to account for distributional asymmetries existing in the time series data, and our empirical analysis is conducted at continental, regional and country-specific levels. Methodologically, our findings indicate that most EKC relationships are found at the tail-end of the quantile regressions, hence demonstrating their usefulness in capturing “hidden relationships” amongst the variables. Empirically, our findings reveal that Southern African countries along the Atlantic Ocean, as well as West African countries which lie along the Gulf of Guinea, tend to have exploitable Fishery-EKC. Conversely, conflict-prone countries found along the Mediterranean Sea, the Indian Ocean and landlocked nations either have inverse or non-existent Fisheries EKC. We provide a novel theoretical explanation for our findings and offer policy recommendations for different stakeholders in African Fisheries markets.

AbstractThe study extends the literature on the nexus between cryptocurrency and uncertainty. This study proxied the cryptocurrencies and global uncertainty, respectively, with the seven most significant and variationally susceptible cryptos and the comprehensive world uncertainty in measuring the crypto-uncertainty nexus over the period (2015–2022) and further employing the quantile regression approach. The OLS model results point to a blend of both significant and insignificant relationship between global uncertainty and cryptocurrencies. These relationships were further examined in quantiles and further accounted for the impact of investor sentiments (VIX) and volatility (OVX), and the results were largely corroborated with the results from the conventional OLS, except for the Bitcoin, Litecoin, and Ripple markets. It was also discovered that the nexus changes across quantiles. The results revealed a blend of strong and weak hedges and safe havens among the selected cryptos against global uncertainty during normal and extreme market conditions. In the face of global turmoil, it was revealed that the average crypto market could serve as a safe haven. Also, the cryptos with an insignificant nexus with global uncertainty were found to be significantly affected by investor sentiment. These findings were further confirmed by the quantile-on-quantile and causality-in-quantile estimations. Given the intense precariousness and lack of hedge and haven capacities within the majority of the cryptocurrencies, it is pertinent for investors to consider the market in general as a means of diversifying their portfolios and reserve the hedge and haven option to the few markets that possess such luxury.

What happens to the impact of tourism on environmental degradation as the income level of the nations or regions increases? The Environmental Kuznets Curve (EKC) hypothesis asserts that the influence of tourism on CO2 emissions decreases with a rise in income levels. This study captures the role of governance in the tourism-induced EKC hypothesis in the European Union (EU), after Brexit. Given that the United Kingdom (UK) is the most visited country in the region, and tourism is a very vital instrument to economic stability and growth, it would be interesting to inspect the relationship among these variables without the UK. Auto-Regressive Distributed Lags (ARDL) estimates show that tourist arrivals decrease carbon emissions in the long-run, while per capita growth fosters carbon emissions in the long-run. In addition, Quantile Regressions (QR) reveal that, in general, the governance indicators have positive effects on emissions. Moreover, for the first quantile, the TEKC emerges. Finally, regarding the causality relationship, a unidirectional relationship from per capita growth to carbon emission, and from carbon emission to tourism arrivals emerge, while no causal link exists between energy consumption and carbon emissions. Moreover, a feedback mechanism (bidirectional causality) is discovered between per capita growth and tourism arrivals, and energy consumption as per capita growth. [ABSTRACT FROM AUTHOR]

There is an urgent need to better understand and predict crop yield responses to weather disturbances, in particular, of extreme nature, such as heavy precipitation events, droughts, and heat waves, to improve future crop production projections under weather variability, extreme events, and climate change. In this paper, we develop quantile regression models for estimating crop yield probability distributions depending on monthly temperature and precipitation values and soil quality characteristics, which can be made available for different climate change projections. Crop yields, historical and those simulated by the EPIC model, are analyzed and distinguished according to their levels, i.e., mean and critical quantiles. Then, the crop yield quantiles are approximated by fitting separate quantile-based regression models. The developed statistical crop yield meta-model enables the analysis of crop yields and respective probabilities of their occurrence as a function of the exogenous parameters such as temperature and precipitation and endogenous, in general, decision-dependent parameters (such as soil characteristics), which can be altered by land use practices. Statistical and machine learning models can be used as reduced form scenario generators (meta-models) of stochastic events (scenarios), as a submodel of more complex models, e.g., Integrated Assessment model (IAM) GLOBIOM. [ABSTRACT FROM AUTHOR]

• An STIRPAT and Different Quantile Regression approaches are applied to test the environmental quality of BRICS countries. • Higher rates of economic and population growth increases carbon emission. • The use of renewable energies and the combined impact of democracy and GDP support cleaner environment. • Bidirectional causality exists between GDP, Democracy, and Population with CO 2 , but one-way causality between clean energy and CO 2. • MM-QR quantile regression test shows more consistent results compared to other quantile approaches, or other panel data approaches. This research explores the nexus of economic expansion, population, use of renewable energy, democracy, and the combined effect of democracy and GDP on carbon dioxide (CO 2) emissions in the BRICS countries. We apply an extended STIRPAT model, including the variables of democracy and democracy with GDP, to examine the case of the BRICS countries between 1990 and 2019. Quantile regression methods (Simultaneous, Powell, and MM-QR) are applied together with the Dynamic OLS (DOLS), Fully modified OLS (FMOLS), and CCR. The results indicate that economic size (GDP) and population are linked to increasing levels of CO 2. Whereas increased use of renewable sources of energy can help reduce environmental degradation. Similarly, an interaction between good democracy and economic growth is helpful for a sustainable environment. The Dumitrescu and Hurlin panel causality test highlights a bidirectional causal link between GDP, Democracy, and Population with CO 2 , but only a unidirectional causal relationship between renewable energy and CO 2. Policymakers in the BRICS countries need to consider:1) pro-growth economic policies along with better democratic practices, 2) higher promotion of renewable energy resources, and 3) improving living standards for the population to achieve higher environmental quality. [ABSTRACT FROM AUTHOR]

There is an urgent need to better understand and predict crop yield responses toweather disturbances, in particular, of extreme nature, such as heavy precipitation events, droughts, and heat waves, to improve future crop production projections under weather variability, extreme events, and climate change. In this paper, we develop quantile regressionmodels for estimating crop yield probability distributions depending on monthly temperature andprecipitation values and soil quality characteristics, which can be made available for different climate change projections. Crop yields, historical and those simulated by the EPIC model, areanalyzed and distinguished according to their levels, i.e., mean and critical quantiles. Then, the crop yield quantiles are approximated by fitting separate quantile-based regression models. Thedeveloped statistical crop yield meta-model enables the analysis of crop yields and respectiveprobabilities of their occurrence as a function of the exogenous parameters such as temperatureand precipitation and endogenous, in general, decision-dependent parameters (such as soil characteristics), which can be altered by land use practices. Statistical and machine learningmodels can be used as reduced form scenario generators (meta-models) of stochastic events(scenarios), as a submodel of more complex models, e.g., Integrated Assessment model (IAM) GLOBIOM. [ABSTRACT FROM AUTHOR]

Many pension reforms in OECD countries included pension statements with the objective of improving individuals' financial security in retirement. Our objective is to assess the effectiveness of the pension information policy implemented in France and to investigate whether the pension statement results in better informed workers, who then increase their retirement savings. Using regression discontinuity designs combined with quantile regressions, we assess whether the changes in retirement savings and holding of assets are due to the pension information system and then quantify the impact. We conclude that a pension estimate sent to workers encourages the wealthiest to increase their retirement savings while it does not influence the savings of individuals with a low level of wealth. [ABSTRACT FROM AUTHOR]

The study extends the literature on the nexus between cryptocurrency and uncertainty. This study proxied the cryptocurrencies and global uncertainty, respectively, with the seven most significant and variationally susceptible cryptos and the comprehensive world uncertainty in measuring the crypto-uncertainty nexus over the period (2015–2022) and further employing the quantile regression approach. The OLS model results point to a blend of both significant and insignificant relationship between global uncertainty and cryptocurrencies. These relationships were further examined in quantiles and further accounted for the impact of investor sentiments (VIX) and volatility (OVX), and the results were largely corroborated with the results from the conventional OLS, except for the Bitcoin, Litecoin, and Ripple markets. It was also discovered that the nexus changes across quantiles. The results revealed a blend of strong and weak hedges and safe havens among the selected cryptos against global uncertainty during normal and extreme market conditions. In the face of global turmoil, it was revealed that the average crypto market could serve as a safe haven. Also, the cryptos with an insignificant nexus with global uncertainty were found to be significantly affected by investor sentiment. These findings were further confirmed by the quantile-on-quantile and causality-in-quantile estimations. Given the intense precariousness and lack of hedge and haven capacities within the majority of the cryptocurrencies, it is pertinent for investors to consider the market in general as a means of diversifying their portfolios and reserve the hedge and haven option to the few markets that possess such luxury. [ABSTRACT FROM AUTHOR]

Human capital in hospitality has been widely addressed by applying sophisticated econometric methods. However, for the Spanish case, there was a gap in the analyses as the crucial importance of collective agreements was undervalued. This paper redesigns the conceptualisation of the variables and applies a subsequent new classification to job positions, as it deals with the outliers at different levels of rigorousness. Then, linearised and quantile regressions were run for each case, obtaining an outcome of thirty values for each variable. The analyses and comparisons show the high importance of collective agreements on salaries, the noticeable low values of human capital variables, and provides additional information for the nationality and gender gaps, the latter strikingly high in upper professional categories. Overall, this paper demonstrates the importance of a proper study design to prevent advanced econometric models from falling into bias and it minimises the differences between methods. [ABSTRACT FROM AUTHOR]

This study estimates the distributional heterogeneity in the effects of climate change on yields of three major cereal crops: rice, maize, and wheat in India using district‐level information for the period 1966–2015. We distinguish between the effects of changes in growing season weather from those due to changes in long‐term climate trends and the heterogeneity in these effects across the distribution of crop yields by estimating naïve and climate penalty inclusive models using fixed‐effect quantile panel models. We observe an absence of adaptation against rising temperatures for rice and wheat. However, we find a statistically significant presence of adaptation for wheat and maize for changes in precipitation, though the magnitude is small. Moreover, we find that the effects are asymmetric, and are larger at the lower tail of productivity distribution and smaller at the upper tail of the distribution. A 1°C increase in temperature lowers rice and wheat productivity by 23% and 9%, respectively at the first quantile, but the damage is only 6% and 5% at the ninth quantile. Heterogeneity in impacts and adaptation estimates over the yield distribution curve and across crops suggests the importance of customizing strategies for adaptation to changing weather and climate conditions across regions, crops, and current productivity levels. [ABSTRACT FROM AUTHOR]

The purpose of our study is to examine the Fishery-based Environmental Kuznets Curve (EKC) for a sample of 48 African countries between 1970–2019. We estimate cubic EKC-type models using quantile regression to account for distributional asymmetries existing in the time series data, and our empirical analysis is conducted at continental, regional and country-specific levels. Methodologically, our findings indicate that most EKC relationships are found at the tail-end of the quantile regressions, hence demonstrating their usefulness in capturing "hidden relationships" amongst the variables. Empirically, our findings reveal that Southern African countries along the Atlantic Ocean, as well as West African countries which lie along the Gulf of Guinea, tend to have exploitable Fishery-EKC. Conversely, conflict-prone countries found along the Mediterranean Sea, the Indian Ocean and landlocked nations either have inverse or non-existent Fisheries EKC. We provide a novel theoretical explanation for our findings and offer policy recommendations for different stakeholders in African Fisheries markets. [ABSTRACT FROM AUTHOR]

• Analysis of links between marriage customs and nutritional status in Indonesia. • Patrilocality is linked to lower BMI in women, suggesting gender discrimination. • Matrilocality is associated with reduced discrimination against women. • Bridewealth practices are associated with higher BMI among both women and men. • Marriage customs should be explicitly considered in nutrition research and policy. Malnutrition remains a serious problem. While various nutrition policies exist, these often fail to consider cultural factors. We contribute to the literature on culture and nutrition, focusing on gendered differences in nutritional investment. Using representative panel data from Indonesia covering a period of 21 years, we analyze how ethnicity-based marriage customs are linked to the body mass index (BMI) of men and women. Patrilocal practices are positively associated with male BMI and negatively associated with female BMI, suggesting discrimination against women. Matrilocal practices are positively associated with female BMI when comparing with women in other cultural settings, but not when comparing with men. The practice of bridewealth is positively associated with male and female BMI when comparing to individuals in settings without this cultural practice. Wherever positive associations between marriage customs and BMI are observed, these are largest for those already overweight, whereas the negative association been patrilocality and female BMI is most pronounced among women who are underweight. Our findings suggest that marriage customs may reinforce nutritional inequalities. A better understanding of such links in different cultural settings is important for effective nutritional policies, especially given that different malnutrition problems coexist in many countries. [ABSTRACT FROM AUTHOR]

• Macroprudential policy has heterogeneous effects on the GDP growth distribution. • The benefits concentrate on the left tail by improving growth-at-risk. • Timing of macroprudential policy is relevant and affects the GDP growth distribution. • Capital measures need to be implemented early enough in the cycle. • Borrower-based measures can be tightened in more advanced stages. I uncover heterogeneous effects of macroprudential policy on GDP growth distribution by bringing together the literature on the impact of macroprudential policy and recent developments on the use of quantile regressions. I identify important benefits of macroprudential policy on the left-tail of the GDP growth distribution which contrast with the negative effects found in previous studies using conditional mean models. These benefits may offset the deterioration on growth-at-risk produced by the build-up of cyclical vulnerabilities and the materialization of financial crises. I also find that the impact of macroprudential policy is dependent on the position in the financial cycle, the type of instrument, and the time elapsed since its implementation. In particular, tightening capital measures during expansions may take up to two years to show evidence of benefits on growth-at-risk, while the positive impact of borrower-based measures is rapidly observed. Conversely, in downturns the benefits of loosening capital measures are more immediate, while those of borrower-based measures are limited. This suggests the importance of timing in macroprudential policy. Overall, this study provides a useful framework to assess the impact of macroprudential policy in terms of GDP growth and to identify the term-structure of specific instruments. [ABSTRACT FROM AUTHOR]

We estimate the wage return of the different university-level educational credentials in Argentina using administrative data for 2019. The results indicate sizeable variability according to the hierarchy of the degree and area of knowledge. Applied Sciences obtain the best results, while the opposite is true for the Humanities. These effects are higher for individuals located in the right tail of the conditional wage distribution. [ABSTRACT FROM AUTHOR]

The digitalization of news and social media provides an unprecedented source to investigate the role of information on market dynamics. However, the observed sentiment time-series represent a noisy proxy of the true investor sentiment. Moreover, modeling the joint dynamics of different sentiment series can be beneficial for the assessment of their economic relevance. The main methodological contribution of this paper is twofold: (i) we filter the latent sentiment signals in a genuinely multivariate model; (ii) we propose a decomposition into a long-term random walk component, named long-term sentiment, and a short-term component driven by a stationary Vector Autoregressive process of order one, named short-term sentiment. The proposed framework is a dynamic factor model describing the joint evolution of the observed sentiments of a portfolio of assets. Empirically, we find that the long-term sentiment co-integrates with the market price factor, while the short-term sentiment captures transient and firm-specific swings. By means of quantile regressions, we assess the significance of the explanatory power of filtered present sentiment on future returns. Then, we demonstrate how the lagged relation can be successfully exploited in a portfolio allocation exercise. [ABSTRACT FROM AUTHOR]

Establishing sustainable and balanced development for green financing is critical for improving financial sustainability and banks' capability. Banks struggle to achieve economic sustainability in the current highly competitive business environment. This research examines the impact of income diversification on financial sustainability proxy by return on assets (ROA) by applying the quantile regression technique to the data from banks of ASEAN countries over the period 2008–2019. In addition, liquidity risk, bank size, interest and non-interest incomes, and market capitalization are studied as control variables. The empirical findings indicate that income diversification positively impacts return on assets at all countries' lower, middle, and upper quantiles, even though sizes can differ across countries and quantiles. Moreover, market capitalization, non-interest income, and banks' size favorably impact banks' performance. In contrast, liquidity risk and interest incomes are negatively linked to the performance of banks for all countries at each quantile. These results have significant strategic implications for managers, regulators, and policymakers who share a common interest in boosting financial sustainability and performance and significantly shaping green recovery. [ABSTRACT FROM AUTHOR]

Latin America experiences an increasing urban primacy index and a rapid expansion of the financial system, putting direct pressure on the demand for resources to satisfy the consumption of large cities. We investigate the convergence of per capita biocapacity in 16 Latin America countries and evaluate the factors that influence its evolution over time. Specifically, we analyze the impact of the urban primacy index, economic progress, and the financial globalization index on the convergence of per capita biocapacity. We use the methodological framework developed by Phillips and Sul Econometrica 75:1771-1855, (2007) to analyze the convergence and the formation of convergence clubs of biocapacity during 1970–2017. The findings indicate that the countries of the region do not share a common trend of biocapacity, although they are grouped into five converging clubs. Biocapacity transition analysis reveals that countries have heterogeneous transition pathways between them. Using marginal effects, we find that the urban primacy index and economic progress reduce the biocapacity. The effect of the financial globalization index on biocapacity is not conclusive. The quantile regressions reveal that quantiles' impact of the urban primacy index and financial globalization on per capita biocapacity is heterogeneous. However, the effect of economic progress on biocapacity that predominates among quantiles is positive. The adoption of common policies among the countries that form the converging clubs could improve the effectiveness of pro-environmental policies and promote the achievement of the Sustainable Development Goals related to environmental quality. [ABSTRACT FROM AUTHOR]

Development aid does not always positively impact economic growth. Instead, aid may decrease total factor productivity (TFP) and discourage the recipient country's own effort to grow. This study contributes to research on macroeconomic aid transmission channels by using panel data from 51 recipient countries over a 36‐year period and applying panel time‐series techniques. The main aim is to study the aid–productivity relation by analyzing the impact of different forms of aid (grants; loans; and bilateral, multilateral, and sector‐related aid) on productivity while accounting for institutional factors and economic policy. The analysis controls for endogeneity and autocorrelation to ensure consistent and efficient estimates. To examine possible vicious circles often attributed to aid, we run quantile regressions to determine the role of aid across productivity quantiles. We find evidence that aid reduced TFP through grants and bilateral aid from 1972 to 1999 and in all quantiles of the TFP distribution from 1972 to 2009. We also find differences in the impact of sector‐related aid, where aid is harmful in more productive countries. [ABSTRACT FROM AUTHOR]

Sustainable Development Goal 10 (SDG10) proposes the reduction of inequalities. This research highlights the importance of considering short- and long-term mechanisms for designing and applying policies to reduce income inequality. Specifically, we test for the causal link between technological innovation and income inequality using a balanced panel data sample from 73 countries worldwide. The inequality–technological innovation relationship is moderated by public spending, manufacturing, employment in agriculture, and export diversification. We use quantile regression techniques to test the impact of technological innovation on income inequality. The results offer robust empirical evidence that in most quantiles, the impact of technological innovation on inequality is positive. This result suggests that the dark side of technological innovation is that it increases income inequality. Furthermore, we find that government spending reduces inequality across all quantiles, while the effect of employment in agriculture and export diversification is inconclusive. Those responsible for social policy towards the achievement of SDG10 must include the advantages of public spending to reduce social disparities and promote social cohesion within countries. [ABSTRACT FROM AUTHOR]

Motivated by empirical reality of differences in the scope and meaning of school choice and private schooling this article focuses on the public demand for increasing diversity of educational options In Europe and the division of public and private provision in it. We aim to test self-interest and ideology-driven logics of education policy preferences in different educational contexts. We operationalize this variety of contexts by the share of private education spending and between-school inequality. We show that, on average, more resourceful individuals are less pro-private-education and those that are ideologically right-leaning are more so. At the system level, private schooling feeds back positively, and this does not differ across educational or ideological divides. Educational inequality, at the same time, de-legitimizes the support for private schooling and its effect differs – higher educated and ideologically right-leaning turn to prefer more public schooling the higher the educational inequality. Thus, the more equal the educational provision, independent of public-private mix, the more entrenched pro-private school preferences will become. [ABSTRACT FROM AUTHOR]

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Globalisation is a prominent driver of wage inequality in advanced economies, and wage differentials paid by the exporter vis‐à‐vis domestically oriented firms play an unmistakable role. In this paper, we measure and decompose the exporter wage gap into several explanatory components by estimating counterfactual distributions for the Spanish economy between 2006 and 2014. To measure the exporter wage gap, an extended Mincer‐type wage equation is estimated along different points of the wage distribution using Unconditional Quantile Regression. Then, we apply the technique of Fortin, Lemieux and Firpo to decompose the exporter wage gap. We find that workers earn higher wages if they work in an exporting firm and that these differences are not constant across the wage distribution: they are greater for middle and middle‐high wages and narrower at the extremes of the distribution. Moreover, the exporter wage gap increased during and after the Great Recession. Characteristics, especially those related to firm and job heterogeneity, play an important role in explaining the gap, mainly in the upper part of the wage distribution. Though in the lower part, wage structure also plays an important role. With some variation across periods, there is a consistent pattern in which occupation, sector and firm size lead to an exporter wage premium resulting in a more unequal wage distribution. These factors are partially compensated by other factors, such as the collective bargaining system. [ABSTRACT FROM AUTHOR]

In this paper, we examine the relationship between fertility and financial development using the National Family Health Survey (NFHS-4) data for the year 2015–2016. We examine the old-age security hypothesis to explain fertility rates amongst Indian women using bank access as a proxy for financial development. As far as we know this paper is the first to look at this relationship the case of India using a quantile count regression. We find that there is a differential effect of access to a bank account on fertility rates amongst Indian women. We find that access to bank accounts increase fertility for the lower conditional quantiles but decreases fertility at the higher conditional quantiles. This study also reiterates that fertility decreases with an increase in education, wealthindex, urbanization and labour participation of women. Financial access has a We also find that infant mortality and age increase fertility rates. The results have some important policy implications. [ABSTRACT FROM AUTHOR]

The World Health Organization proclaimed the global epidemic of obesity more than twenty years ago. However, there has never been a coordinated action to address the problem on the global level. Covid-19 virus pandemic is world's largest public health problem currently. Many comorbidities associated with Covid-19 and obesity mortality are common. We determine that obesity is single largest and most common cause of mortality in Covid-19 patients globally based on a sample of 171 countries, while economic variables have no impact. This creates an opportunity to finally address the obesity global epidemic through an effort coordinated on the global level. [ABSTRACT FROM AUTHOR]

The heterogeneous economic results of divorce have received limited attention. The current study analyzes such consequences from an intersectionality perspective, where heterogeneity is expressed not only in gender groups, but also in the locations of women and men on the earnings distribution scale. We also examine whether remarriage and welfare support have differing effects on income across these groups. The study uses a unique dataset in Israel that merges administrative data from the tax authorities (employment income and pensions) with the National Insurance Institute database (socio-demographic information and allowances). Applying two-level ("mixed") panel models combined with quantile regressions, we investigate the post-divorce income of women and men by tertile, as well as in the top percentile of each gender group. Results show that the most vulnerable group among men is low income, while the most immune group of men is very high income. For women, however, differences between classes are small; across the board, women's post-divorce income decreases by at least a third. Thus, while the effect of divorce on men's income depends upon their earnings level, its effect on women's income is negative even in the top percentile. Remarriage has a differential effect on income based on location on the income distribution scale only for men. The welfare policy effect on income is gendered: regardless of earnings group, allowances are negatively related to income for women and positively related for men. [ABSTRACT FROM AUTHOR]