Matching has become a popular approach to estimate average treatment effects. It is based on the conditional independence or unconfoundedness assumption. Checking the sensitivity of the estimated results with respect to deviations from this identifying assumption has become an increasingly...

This paper re-examines inference for cluster samples. Sensitivity analysis is proposed as a new method to perform inference when the number of groups is small. Based on estimations using disaggregated data, the sensitivity of the standard errors with respect to the variance of the cluster...

Assuming a normal-Wishart modelling framework we compare two methods for finding outliers in a multivariate regression (MR) system. One method is the add-1-dummy approach which needs fewer parameters and a model choice criterion while the other method estimates the outlier probability for each...

Sensitivity analysis studies how the variation in the numerical output of a model can be quantitatively apportioned to different sources of variation in basic input parameters. Thus, it serves to examine the robustness of numerical results with respect to input parameters, which is a...

This paper focuses on firm valuation for tax purposes of non-listed company shares and its sensitivity towards different market conditions. Since the value of a private company cannot be observed on the stock market the value has to be estimated. Due to uncertainty, expected future profits may...

The paper shows the ways of disclosing financial risks by IFRS 7 and certain types of sensitivity analysis. The different possibilities of preparing a sensitivity analysis, such as value at risk are illustrated and their suitability for reporting are faced critically. Following, the manner of...

The combination of experts' probability distributions involved in a due diligence is valuable for encapsulating the accumulated information for decision makers and providing the current state of expert opinion regarding important uncertainties. Therefore, this paper shows how to create and...

Quantiles play an important role in modelling quality of service in the service industry and in modelling risk in the financial industry. Recently, Hong showed in his breakthrough papers that efficient simulation based estimators can be obtained for quantile sensitivities by means of sample path...

This paper examines how robust economic, political, and demographic variables are related to water and air pollution. Employing Bayesian Averaging of Classical Estimates (BACE) for a cross section of up to 74 countries, 33 variables and 3 proxies for air and water pollution over a period from...

Recent literature proposes many variables as significant determinants of pollution. This paper gives an overview of this literature and asks which of these factors have an empirically robust impact on water and air pollution, i.e. do not depend upon the conditioning information set. For this, we...