The procedures of estimating prediction intervals for ARMA processes can be divided into model based methods and empirical methods. Model based methods require knowledge of the model and the underlying innovation distribution. Empirical methods are based on the sample forecast errors. In this...

The choice of a smoothing parameter or bandwidth is crucial when applying non- parametric regression estimators. In nonparametric mean regression various meth- ods for bandwidth selection exists. But in nonparametric quantile regression band- width choice is still an unsolved problem. In this...

We propose a novel empirical approach to inform monetary policymakers about the potential effects of policy action when facing trade-offs between financial and macroeconomic stability. We estimate a quantile vector autoregression (QVAR) for the euro area covering the real economy, monetary...

Overlapping portfolios constitute a well-recognised source of risk, providing a channel for financial contagion induced by the market price impact of asset deleveraging. We introduce a novel method to assess the market price impact on a security-by-security basis from historical daily traded...

We develop inference procedures for policy analysis based on regression methods. We consider policy interventions that correspond to either changes in the distribution of covariates, or changes in the conditional distribution of the outcome given covariates, or both. Under either of these policy...

The influence of maternal health problems on child's worrying status is important in practice in terms of the intervention of maternal health problems early for the influence on child's worrying status. Conventional methods apply symmetric prior distributions such as a normal distribution or a...

Analyzing a comprehensive database of limited liability manufacturing firms this paper investigates the relation between a firm’s financial situation and its conditional expected growth rate. Specifically, using quantile regressions, we obtain a quantitative characterization of this relation...

In this paper, we develop a state-dependent sensitivity value-at-risk (SDSVaR) approach that enables us to quantify the direction, size, and duration of risk spillovers among financial institutions as a function of the state of financial markets (tranquil, normal, and volatile). Within a system...