We propose and apply a new approach for analyzing the effects of fiscal policy using vector autoregressions. Unlike most of the previous literature this approach does not require that the contemporaneous reaction of some variables to fiscal policy shocks be set to zero or need additional...

This paper proposes a test for missing at random (MAR). The MAR assumption is shown to be testable given instrumental variables which are independent of response given potential outcomes. A nonparametric testing procedure based on integrated squared distance is proposed. The statistic’s...

To explore how occurring critical incidents affect customer-brand relations, this study measures the impact on the basis of an online experiment. For this purpose, 1,122 usable responses are gathered considering the smartphone brands of Apple and Nokia as well as different scenarios. The...

This paper considers estimation and inference for varying-coefficient models with nonstationary regressors. We propose a nonparametric estimation method using penalized splines, which achieves the same optimal convergence rate as kernel-based methods, but enjoys computation advantages. Utilizing...

We consider noisy non-synchronous discrete observations of a continuous semimartingale. Functional stable central limit theorems are established under high-frequency asymptotics in three setups: onedimensional for the spectral estimator of integrated volatility, from two-dimensional asynchronous...

This paper proposes a new econometric approach to disentangle two distinct response patterns of the yield curve to monetary policy announcements. Based on cojumps in intraday tick-data of a short and long term interest rate, we develop a day-wise test that detects the occurrence of a significant...

We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semi-martingale log asset price process which is subject to noise and non-synchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance...

Given a random sample from some unknown density f0 : R → [0;∞) we devise Haar wavelet estimators for f0 with variable resolution levels constructed from localised test procedures (as in Lepski, Mammen, and Spokoiny (1997, Ann. Statist.)). We show that these estimators adapt to spatially...