part of HFCS. We apply the calibration method of Blanchet, Flores and Morgan (2022), but propose a new way to determine the … merging point where the calibration starts. Calibrated weights are then used with HFCS wealth values. We test the method on … Austrian data and find that calibration increases the top 1 % wealth share from 26 % to 37 % in 2014 and from 23 % to 27 % in …

COVID-19 observations and discusses their impact on prior calibration for inference and forecasting purposes. It shows that …-section of information is used. Besides the error structure, this paper shows that the standard Minnesota prior calibration is an … nominal variables. To alleviate this sensitivity, an outlier-robust prior calibration is proposed. …

We propose a general protocol for calibration and validation of complex simulation models by an approach based on …

A new approach, derived from the equal expected impact (EEI) approach, was used for the calibration of the buffers for … to the EEI approach as used for the updated calibration. First, we explain the economic intuition and the theoretical … operationalisation. Finally, we discuss limitations of the EEI approach and specify issues to be addressed in future calibration …

. The linear logistic regression has developed into a standard calibration approach in the banking sector. With the advent … of machine learning techniques in the discriminatory phase of credit risk models, however, the standard calibration … critics with a target. Previous literature has converted the calibration problem into a regression task without any loss of …

We aim to assess the impact of a pandemic data point on the calibration of a stochastic multi-population mortality … buckets. To be compliant with the design and calibration strategy of the Li and Lee model, we transform the weekly mortality …, like COVID-19 in the year 2020, we weigh this data point in either the calibration or projection step. Obviously, the more …

biased. Using a Bavarian farm sample, the present study shows how the so-called calibration approach, utilising auxiliary …

. The linear logistic regression has developed into a standard calibration approach in the banking sector. With the advent … of machine learning techniques in the discriminatory phase of credit risk models, however, the standard calibration … critics with a target. Previous literature has converted the calibration problem into a regression task without any loss of …