This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and suggests the use of devolatized returns computed as returns standardized by realized volatilities rather than by GARCH type volatility estimates. The t-DCC...

Recent work on social status led to derivation of a new continuous distribution based on the exponential. The new variate, termed the ring(2)-exponential, in turn leads to derivation of two closely-related new families of continuous distributions, which we call the mirror-exponential and the...

Estimation of average treatment effects under unconfoundedness or exogenous treatment assignment is often hampered by lack of overlap in the covariate distributions. This lack of overlap can lead to imprecise estimates and can make commonly used estimators sensitive to the choice of...

This paper uses data on currency options prices for the exchange rates of the three largest new EU member states Poland, Czech Republic and Hungary vis-a-vis the euro and the US dollar to estimate the risk-neutral density (RND) functions and the density interval bands. Analysing the RNDs, we...

This paper reviews recently proposed likelihood ratio tests of goodness-of-fit and independence of interval forecasts. It recasts them in the framework of Pearson chi-squared statistics, and considers their extension to density forecasts and their exact small-sample distributions. The use of the...

In this paper nonparametric instrumental variable estimation of local average treatment effects (LATE) is extended to incorporate confounding covariates. Estimation of local average treatment effects is appealing since their identification relies on much weaker assumptions than the...

Propensity score matching is widely used in treatment evaluation to estimate average treatment effects. Nevertheless, the role of the propensity score is still controversial. Since the propensity score is usually unknown and has to be estimated, the efficiency loss arising from not knowing the...

I propose a new model, conditional quantile regression (CQR), that generates density forecasts consistent with a specific view of the future evolution of some variables. This addresses a shortcoming of existing quantile regression-based models, for example the at-risk framework popularised by...

After the Chain-Ladder and the Bornhuetter-Ferguson method, the Cape-Cod reserving method is among the most popular methods used to project non-life paid or incurred triangles. For this method, A. Saluz (2015) developed a stochastic model allowing the estimation of the prediction error resulting...

We propose a new regression method to estimate the impact of explanatory variables on quantiles of the unconditional (marginal) distribution of an outcome variable. The proposed method consists of running a regression of the (recentered) influence function (RIF) of the unconditional quantile on...