This study aims to determine the most important component of economic freedom and to rank the performance of countries using multiple criteria decision-making tools within the context of fuzzy set theory. To do so, we utilize a combination of fuzzy entropy weighting and fuzzy technique for order...

This study investigates systemic risk, return patterns, and diversification within the Johannesburg Stock Exchange (JSE) during the COVID-19 pandemic, utilizing data-centric approaches and the ARMA-GARCH vine copula-based conditional value-at-risk (CoVaR) model. By comparing three investment...

Multiple job holding (MJH) is increasingly frequent in industrialized countries. Individuals holding a secondary job add to their experience, skills, and networks. We study the long-run labor market outcomes after MJH and investigate whether career effects can be validated. We employ...

Multiple job holding (MJH) is increasingly frequent in industrialized countries. Individuals holding a secondary job add to their experience, skills, and networks. We study the long-run labor market outcomes after MJH and investigate whether career effects can be validated. We employ...

For the last 50 years or so, the efficient market hypothesis (EMH) has been the central pillar of economic thought and the building block of portfolio theory. However, the validity of the EMH still remains controversial, and the methods of testing for market efficiency have been criticised. This...

Job training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of...

Job training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of...

Job training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of...

In this paper, we attempted to expand the Frechet distribution by employing the T-X family of distributions and named the newly formulated model Extended odd Frechet-exponential distribution (EOFED). Several structural properties, reliability measurements and characteristics were estimated and...

This paper proposes nonparametric estimates for the two information measures extropy and entropy when a progressively Type-I interval censored data is available. Different nonparametric approaches are used for deriving the estimates, including: moments of the empirical cumulative distribution...

Financial institutions should prioritize the adoption of comprehensive Environmental, Social, and Corporate Governance (ESG) disclosure policies to improve their market reputation and decrease capital expenditures. The current study's research objective is to investigate the impact of both...

We present a geometric approach to the finite Rational Inattention (RI) model, recasting it as a convex optimization problem with reduced dimensionality that is well suited to numerical methods. We provide an algorithm that outperforms existing RI computation techniques in terms of both speed...

People with Parkinson's Disease (PD) might struggle with sadness, restlessness, or difficulty speaking, chewing, or swallowing. A diagnosis can be challenging because there is no specific PD test. It is diagnosed by doctors using a neurological exam and a medical history. This study proposes...

This study examines the market efciency in the prices and volumes of transactions of 41 cryptocurrencies. Specifcally, the correlation dimension (CD), Lyapunov Exponent (LE), and approximate entropy (AE) were estimated before and during the COVID-19 pandemic. Then, we applied Student's t-test...

Purpose - We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Design/methodology/approach - We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy....

This paper aims to investigate the drivers of inequality of opportunity in health outcome among children below 5 years of age, using the Tunisian 2018 Multiple Indicator Cluster Survey. This study adopts the general entropy measures to examine the pattern of child health inequality. The results...

This study addresses market concentration among major corporations, highlighting the utility of relative entropy for understanding diversification strategies. It introduces entropic value at risk (EVaR) as a coherent risk measure, which is an upper bound to the conditional value at risk (CVaR),...

Bayes' theorem incorporates distinct types of information through the likelihood and prior. Direct observations of state variables enter the likelihood and modify posterior probabilities through consistent updating. Information in terms of expected values of state variables modify posterior...

In this paper, the copula theory is used to describe the dependence structure between variables, while the information theory provides the tools necessary to measure the uncertainty associated with these variables. What both theories have in common is copula entropy, which is strictly related to...

Existing probabilistic hesitant fuzzy set (PHFS) measures are constructed using two information measures: hesitancy and unwrapped probabilities. We argue that unifying these semantic terms in PHFS information theory is not logical. We introduce a new class of information measures for PHFSs,...

Building on the success of Ferreira and Santa-Clara (2011) in separately forecasting the return components of the stock market, this paper examines the links between economic regimes and these components to predict the aggregate U.S. stock market. We propose a three-step methodology that we call...