In this paper we propose a downside risk measure, the expectile-based Value at Risk (EVaR), which is more sensitive to the magnitude of extreme losses than the conventional quantile-based VaR (QVaR). The index $\theta$ of an EVaR is the relative cost of the expected margin shortfall and hence...

In the finance literature, statistical inferences for large-scale testing problems usually suffer from data snooping bias. In this paper we extend the quot;superior predictive abilityquot; (SPA) test of Hansen (2005, JBES) to a stepwise SPA test that can identify predictive models without...

We consider a functional parameter called the conditional average treatment effect (CATE), designed to capture heterogeneity of a treatment effect across subpopulations when the unconfoundedness assumption applies. In contrast to quantile regressions, the subpopulations of interest are defined...

This paper examines the distribution structural functions (DSFs) and quantile structural functions (QSFs) in a semiparametric treatment effect model. The DSF and QSF are defined as the distribution function and quantile function of the counterfactural outcome when covariates are exogenously...

This paper considers methods for comparing poverty in two income distributions. We …first discuss the concept and usefulness of the Poverty Gap Pro…le (PGP) for comparing poverty in two populations. Dominance of one PGP over another suggests poverty dom- inance for a wide class of indices...

We propose inverse probability weighted estimators for the distribution functions of the potential outcomes under the unconfoundedness assumption and apply the inverse mapping to obtain the quantile functions. We show that these estimators converge weakly to zero mean Gaussian processes. A...