Researchers frequently test identifying assumptions in regression based research designs (which include instrumental variables or difference-in-differences models) by adding additional control variables on the right hand side of the regression. If such additions do not affect the coefficient of...

High-frequency financial data allow us to estimate large volatility matrices with relatively short time horizon. Many novel statistical methods have been introduced to address large volatility matrix estimation problems from a high-dimensional Ito process with microstructural noise...

Recent literature has suggested many ways of measuring equality of opportunity. We analyze in a systematic manner the various approaches put forth in the literature to show whether and to what extent different choices matter empirically. We use EU-SILC data for most European countries for 2005...

The model parameters of linear state space models are typically estimated with maximum likelihood estimation, where the likelihood is computed analytically with the Kalman filter. Outliers can deteriorate the estimation. Therefore we propose an alternative estimation method. The Kalman filter is...

Prediction of future movement of stock prices has been the subject matter of many research work. On one hand, we have proponents of the Efficient Market Hypothesis who claim that stock prices cannot be predicted accurately. On the other hand, there are propositions that have shown that, if...

A proper modeling of the long-run behavior of energy and oil intensities is crucial for many reasons. This paper aims at checking whether this long-run behavior should be modelled as a deterministic or a stochastic trend, or both. We firstly apply a test for a deterministic trend robust to...