Advice plays a central role in health, personal finance, and energy-efficiency decisions. We study how a benevolent expert should design verifiable advice - such as whether to commission a diagnostic test of different accuracy - when the agent is behaviorally biased, either neglecting...

It is well known that standard frequentist inference breaks down in IV regressions with weak instruments. Bayesian inference with diffuse priors suffers from the same problem. We show that the issue arises because flat priors on the first-stage coefficients overstate instrument strength. In...

This paper estimates Morocco's natural interest rate (NIR) using two approaches: a standard HLW-type framework and an augmented specification that incorporates external factors, namely imported inflation, and movements in the real effective exchange rate. The results point to a downward trend in...

The output gap is a key guide for economic policymaking and analysis. It is often used to quantify inflationary pressures and thus plays a central role in Danmarks Nationalbank's assessment of the state of the Danish economy. This paper refines Danmarks Nationalbank's existing production...

This work presents a practical approach to improve risk quantification for heavy-tailed insurance claims through model averaging and grid map visualization, addressing the drawbacks of traditional single "best" model selection commonly used in actuarial and model-fitting literature. This is a...

We introduce a novel methodology, "parametric tilting," for incorporating external information into econometric model-based density forecasts. Unlike traditional entropic tilting, which can generate unrealistic or unstable distributions under certain conditions, parametric tilting ensures more...

In this paper, the geometric distribution parameter is estimated under a type-I censoring scheme by means of the Bayesian estimation approach. The Beta and Kumaraswamy informative priors, as well as five loss functions are used for this purpose. Expressions of Bayes estimators and Bayes risks...

Conventional risk assessment frameworks usually define risk as a function of vulnerabilities and threats, but they frequently lack a single quantitative model that incorporates the unique features of each element. In order to close this gap, this paper creates a flexible, open, and theoretically...

This study examines the relationship between environmental innovation and firm valuation between 2019 and 2023, within a broader framework that includes governance and macroeconomic variables. This study employs Bayesian model averaging and random forest methodologies to analyse how...

In this work, we study n-agent Bayesian games with m-dimensional vector types and linear payoffs, also called linear multidimensional Bayesian games. This class of games is equivalent with n-agent, m-game uniform multigames. We distinguish between games that have a discrete type space and those...

In a stage of more and more complex and high-frequency financial markets, the volatility analysis is a cornerstone of modern financial econometrics with practical applications in portfolio optimization, derivative pricing, and systematic risk assessment. This paper introduces a novel Bayesian...

Financial time-series data often exhibit statistically significant skewness and heavy tails, and numerous flexible distributions have been proposed to model them. In the context of the Log-linear Realized GARCH model with Skew-t (ST) distributions, our objective is to explore how the choice of...

Recent advances in healthcare technologies have led to the availability of large amounts of biological samples across several techniques and applications. In particular, in the last few years, Raman spectroscopy analysis of biological samples has been successfully applied for early-stage...

This paper explores classical and Bayesian approaches to the estimation of unknown parameters and reliability functions for the power Rayleigh distribution. The maximum likelihood estimator (MLE) method is considered in classical estimation. The Bayesian estimation, on the other hand uses...

We present a comprehensive meta-analysis of the determinants of financial inclusion, synthesizing 3,817 estimates from 102 studies published between 2013 and 2024. To reconcile divergent findings, we convert all results to a common unbiased metric-the partial correlation coefficient corrected...

Model misspecification in multivariate econometric models can strongly influence estimates of quantities of interest such as structural parameters, forecast distributions or responses to structural shocks, even more so if higher-order forecasts or responses are considered, due to parameter...

Modeling loss data is a crucial aspect of actuarial science. In the insurance industry, small claims occur frequently, while large claims are rare. Traditional heavy-tail distributions, such as Weibull, Log-Normal, and Inverse Gaussian distributions, are not suitable for describing insurance...