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The demographic risk is the risk due to the uncertainty in the demographic scenario assumptions by which life insurance products are designed and valued. The uncertainty lies both in the accidental (insurance risk) and systematic (longevity risk) deviations of the number of deaths from the value anticipated for it. This last component gives rise to the risk due to the randomness in the choice of the survival model for valuations (model risk or projection risk). If the insurance risk component can be assumed negligible for well‐diversified portfolios, as in the case of pension annuities, longevity risk is crucial in the actuarial valuations. The question is particularly decisive in contexts in which the longevity phenomenon of the population is strong and pension annuity portfolios constitute a meaningful slice of the financial market – both typical elements of Western economies. The paper aims to focus on the solvency appraisal for a portfolio of life annuities, deepening the impact of the demographic risk according to suitable risk indexes apt to describe its evolution in time.

The financial quantity proposed for representing the economic wealth of the life insurance company is the stochastic surplus, and the paper analyses the impact on it of different demographic assumptions by means of risk indicators as the projection risk index, the quantile surplus valuation and the ruin probability. By means of the proposed models, the longevity risk is mainly taken into account in a stochastic scenario for the financial risk component, in order to consider their interactions, too. In order to furnish practical details significant in the portfolio risk management, several numerical applications clarify the practical meaning of the models in the solvency context.

This paper studies the impact on the portfolio surplus of the systematic demographic risk, taking into account their interaction with the financial risk sources. In this order of ideas, the internal risk profile of a life annuity portfolio is deeply investigated by means of suitable risk indexes: in a solvency analysis perspective, some possible scenarios for the evolution of death rates (generated by different survival models) are considered and this paper evaluates the impact on the portfolio surplus caused by different choices of the demographic model. The first index is deduced by a variance decomposition formula, the other ones involve the conditional quantile calculus and the ruin probability. Such indexes constitute benchmarks, whose conjoined use provides useful information to the meeting of the solvency requirements.

With respect to the recent actuarial literature, in which the most important contribution on the surplus analysis has been given by Lisenko et al. – where the analysis focuses on the financial aspect applied to portfolios of temporary and endowment contracts – the paper considers life annuity portfolios, taking into account the effect of the systematic demographic risk and its interactions with the financial risk components.

Most epidemic transmission forecasting methods can only provide deterministic outputs. This study aims to show that probabilistic forecasting, in contrast, is suitable for stochastic demand modeling and emergency medical resource planning under uncertainty.

Two probabilistic forecasting methods, i.e. quantile regression convolutional neural network and kernel density estimation, are combined to provide the conditional quantiles and conditional densities of infected populations. The value of probabilistic forecasting in improving decision performances and controlling decision risks is investigated by an empirical study on the emergency medical resource planning for the COVID-19 pandemic.

The managerial implications obtained from the empirical results include (1) the optimization models using the conditional quantile or the point forecasting result obtain better results than those using the conditional density; (2) for sufficient resources, decision-makers' risk preferences can be incorporated to make tradeoffs between the possible surpluses and shortages of resources in the emergency medical resource planning at different quantile levels; and (3) for scarce resources, the differences in emergency medical resource planning at different quantile levels greatly decrease or disappear because of the existing of forecasting errors and supply quantity constraints.

Very few studies concern probabilistic epidemic transmission forecasting methods, and this is the first attempt to incorporate deep learning methods into a two-phase framework for data-driven emergency medical resource planning under uncertainty. Moreover, the findings from the empirical results are valuable to select a suitable forecasting method and design an efficient emergency medical resource plan.

The main purpose of this paper is to investigate the sheepskin effects in the returns to education in the Sri Lankan labor market by ethnicity.

The study is based on the latest Sri Lankan Consumer Finance and Socio‐economic Survey. The study employs the quantile regression method for each conditional quantile wage group, rather than the mean regression analysis used in most labor market analysis. The quantile regression technique fits hyperplanes through out the conditional wage and is ideal for characterizing the entire wage distribution. The standard Mincerian wage equation was estimated for the full sample of male workers and separately for the two main ethnic groups in Sri Lanka.

The empirical findings are broadly encouraging. Quantile regression results suggest that average returns to education for both ethnic groups differs significantly from the returns at the two extreme ends of the wage distribution. In general, the returns to education are positive for both groups, but the returns are higher for Sinhalese workers than for Tamil. An increasing trend in returns to education is evident for both ethnic groups when moving up wage distribution. Sinhalese workers experience higher returns to education than for Tamil especially at the bottom of the wage distribution, but the difference becomes less at the upper part of the distribution. Estimated results with spline in years of education suggest that returns to secondary education are higher for Sinhalese workers, but the returns to tertiary education are greater for Tamil workers at the upper part of the wage distribution. Findings indicate that returns to experience are also higher for Sinhalese workers than for Tamil workers.

This is the first study that examines sheepskin effects in the returns to education by ethnicity in Sri Lanka in a Mincerian framework, employing quantile regression models.

High economic policy uncertainty forces firms to accumulate a higher level of cash than during normal business periods. However, it is not evident that economic policy uncertainty has a homogeneous impact across cash-holding distributions. This paper aims to study the impact of economic policy uncertainty, leverage and their interaction on cash-holding distributions.

This study adopted a quantile regression approach to examine the influence of economic policy uncertainty and firm leverage on firm-level cash-holding distributions. To investigate the influence across quantiles, the author estimated 19 quantiles between 0.05 and 0.95.

This study finds that both economic policy uncertainty and firm leverage significantly affect firm-level cash-holding distributions heterogeneously. But, the impact of the interaction of these two variables is significant only for firms placed in the 60th to 85th quantiles of cash holding distribution.

The study adds to the existing knowledge of determinants of firm-level cash holdings but takes exogenous variables as economic policy uncertainty. The paper builds on a unique sample setting wherein, the cash holdings of all nonfinancial firms have increased many folds, including housing companies in an emerging economy.

Due to their limited capacity for adaptation and dependence on natural resources for economic growth, developing countries (DCs) tend to be more prone to climate change. It is argued that climate finance (CF) is a significant financial innovation to mitigate the negative effects of climate variation. However, the heterogeneous impacts of CF on environmental sustainability (ES) and social welfare (SW) have been masked. Thus, this study aims to investigate the heterogeneous effects of CF on ES and SW in 80 CF receipt DCs from 2002 to 2018. This study also aims to investigate the effects of CF on ES and SW based on population size, income heterogeneity and the type of CF.

The method of moments quantile regression (MMQR) with fixed effects is utilized. Alternatively, the fully modified least square (FMOLS) and dynamic least square (DOLS) estimators are used for the robustness test.

The findings revealed that DCs with the lowest and middle quantiles of EF, carbon dioxide (CO₂) emissions and human development exhibit large beneficial impacts of CF on ES and SW. In contrast, the positive effects of CF on ES breakdown for countries with the largest distributions of EF and CO₂ emissions. Besides, the impacts of CF on ES and SW depend on income heterogeneity, population size and the type of CF.

This study calls for a framework to integrate CF into all economic development decisions to strengthen climate-resilient SW and ES in DCs.

To the best of the authors’ knowledge, this is the first study to investigate the effects of CF on ES and SW in a wide range of DCs. Thus, it complements existing related literature focusing on the effects of CF on ES and SW.

The issue of which financial initial conditions are necessary to materialize the benefits of financial globalization remains open to debate in the literature. In this paper, the author tries to put some empirical structure on the concept of financial threshold conditions in order to give policymakers guidance on the Kose et al. and Henry hypothesis. Its object is to assess whether financial benefits of financial globalization are questionable until greater domestic financial development has taken place in African countries. The paper aims to discuss these issues.

In framing the financial dimension in a more concrete and tractable manner, the author examines the concerns of how domestic financial initial dynamics of depth (economic and financial systems), efficiency (banking and financial systems), activity (banking and financial systems) and size, play out in the financial development benefits of financial globalization. The estimation approach consists of assessing the impact of financial globalization through out the conditional distributions of domestic financial development dynamics.

The introduction of previously missing financial dimensions into the debate generates a number of important findings. Only financial initial (threshold) conditions of size are necessary to materialize the benefits of financial globalization. While financial depth only partially validates the hypothesis, dynamics of efficiency and activity (credit) do not confirm the hypothesis.

Addressing the issue of surplus liquidity in African financial institutions could improve the benefits of financial size and potentially reverse the trends of financial efficiency and activity. Depending on the context of sampled countries, the appropriate role of policy has always been either to stem the tide of capital flows or encourage them. Policymakers who have been viewing their challenges exclusively from the latter perspective for benefits in growth (finance) might be getting the financial dynamics badly wrong.

Blanket financial development policies may not reap the financial benefits of financial globalization until domestic financial dynamics of depth, efficiency, activity and size are critically considered. The introduction of the last three previously missing components in the literature sheds more light on the globalization-development nexus.

The authors target the interrelationships between non-fungible tokens (NFTs), decentralized finance (DeFi) and carbon allowances (CA) markets during 2021–2023. The recent shift of crypto and DeFi miners from China (the People's Republic of China, PRC) green hydro energy to dirty fuel energies elsewhere induces investments in carbon offsetting instruments; this is a backdrop to the authors’ investigation.

The quantile vector autoregression (VAR) approach is employed to examine extreme-quantile-connectedness and spillovers among the NFT Index (NFTI), DeFi Pulse Index (DPI), KraneShares Global Carbon Strategy ETF price (KRBN) and the Solactive Carbon Emission Allowances Rolling Futures Total Return Index (SOLCARBT).

At bull markets, DPI is the only consistent net shock transmitter as NFTI transmits innovations only at the most extreme quantile. At bear markets, KRBN and SOLCARBT are net shock transmitters, while NFTI is the only consistent net shock receiver. The receiver-transmitter roles change as a function of the market conditions. The increases in the relative tail dependence correspond to the stress events, which make systemic connectedness augment, turning market-specific idiosyncratic considerations less relevant.

The shift of digital asset miners from the PRC has resulted in excessive fuel energy consumption and aggravated environmental consequences regarding NFTs and DeFi mining. Although there exist numerous studies dedicated to CA trading and its role in carbon print reduction, the direct nexus between NFT, DeFi and CA has never been addressed in the literature. The originality of the authors’ research consists in bridging this void. Results are valuable for portfolio managers in bull and bear markets, as the authors show that connectedness is more intense under such conditions.

The purpose of this paper is to analyse the role of performance-related pay (PRP) on productivity and wages of Italian firms.

A unique data set for the Italian economy, obtained from the ISFOL Employer and Employee Surveys (2005, 2007, 2010), is used to estimate the relationship between PRP, labour productivity and wages, also controlling for an ample set of covariates. The authors performed standard quantile regressions (QRs) to investigate heterogeneity in associations of PRP with labour productivity and wages. In a second stage, the endogeneity of PRP was taken into account by using instrumental variable QR techniques.

The econometric estimates suggests that PRP are incentive schemes that substantially lead to efficiency enhancements and wage gains. These findings are confirmed for firms under union governance and suggest that well-designed policies, that circumvent the limited implementation of PRP practices, would guarantee productivity improvement and wage premiums for employees.

The main limitation of the findings concerns PRP data, that do not offer statistical information on different types of schemes, at group or individual level.

This paper is the first to investigate, on a national scale for the Italian economy, the role of PRP on both productivity and wages, in order to shed light on the efficiency and distributive implications, whereas most of the studies of related literature are restricted to one of those aspects.

The purpose of this paper is to study the influence of financial flexibility (FF) on enterprise performance (EP) within Taiwan’s hospitality industry during the COVID-19 shock and explore whether EP varies with hospitality industry characteristics.

Secondary data of 39 Taiwan Stock Exchange-listed hospitality firms were collected from the Taiwan Economic Journal databases. Quantile regression analysis was applied to examine the FF-EP relationship

The results evidence that there is a U-shaped (convex) FF-EP relationship for hospitality firms in the 10th, 25th and 50th Tobin’s Q quantiles and in asset-heavy firms. For asset-light firms, FF has an inverted U-shaped (concave) effect on EP in the 90th Tobin’s Q quantile

The empirical results highlight the need for Taiwan’s hospitality industry as a whole to take rolling adjustment and optimization of FF and concentrate on liquidity risk management after the COVID-19 pandemic and for long-term sustainability.

To the best of the authors’ knowledge, this study is one of the first to examine the nonlinear FF-EP relationship in the hospitality industry of Taiwan, particularly amid the COVID-19 shock. Moreover, this study extends current literature by revealing the hospitality industry’s FF-EP relationship and highlights the importance of the pandemic crisis context.

This paper aims to provide an empirical analysis of the macroeconomic determinants of sovereign bond yield spreads in the Eurozone from 2000 until August 2012, when the Outright Monetary Transactions programme was launched.

The authors constructed an unbalanced panel with quarterly data from 2000 Q1 to 2012 Q2 for the 12 Eurozone countries: Austria, Belgium, Finland, France, Germany, Greece, Ireland, Luxembourg, Italy, The Netherlands, Portugal and Spain. The authors propose a model that explains spreads through the main categories of variables observed in the literature. The relationship between variables is analysed using ordinary least squares and quantile regressions. As discussed by the authors, quantile regressions provide a more precise estimation, given the huge heterogeneity across counties that can be observed in the Eurozone.

Results show that the relationship between sovereign risk and macroeconomic fundamentals is affected by a strong country sentiment effect. The impact of country sentiment on sovereign risk is larger for those countries that were already experiencing higher spreads. Regardless the impact that European Central Bank’s (ECB) intervention had on sovereign risk from 2012, quantile regression results suggest that policy recommendations and goals should be adapted to each country’s market perception.

The results obtained improve on previous findings on this topic (De Grauwe and Ji, 2012) in two ways. First, they show that even introducing every category of determinants found in the literature in the main specification, fundamentals can only partially explain the evolution of sovereign risk in the Eurozone. Second, they find there is a country-sentiment effect that affects the relationship between macroeconomic indicators and sovereign risk. Furthermore, the paper finds that the country-sentiment effect is larger for countries facing high spreads.