The current economic crisis requires fast information to predict economic behavior early, which is difficult at times of structural changes. This paper suggests an innovative new method of using data on internet activity for that purpose. It demonstrates strong correlations between keyword...

We show that the main nonparametric identification finding of Abbring and Van den Berg (2003b, Econometrica) for the effect of a timing-chosen treatment on an event duration of interest does not hold. The main problem is that the identification is based on the competing-risks identification...

We propose a specification test for a wide range of parametric models for the conditional distribution function of an outcome variable given a vector of covariates. The test is based on the Cramer-von Mises distance between an unrestricted estimate of the joint distribution function of the data,...

This paper establishes stylized facts about the cyclicality of real consumer wages and real producer wages in Germany. As detrending methods we apply the deterministic trend model, the Beveridge-Nelson decomposition, the Hodrick-Prescott filter, the Baxter-King filter and the structural time...

In this paper we have examined the unemployment rate series in Turkey by using long memory models and in particular employing fractionally integrated techniques. Our results suggest that unemployment in Turkey is highly persistent, with orders of integration equal to or higher than 1 in most...

In 2002 we published a paper in which we used state space time series methods to analyse the teenage employment‐federal minimum wage relationship in the US (Bazen and Marimoutou, 2002). The study used quarterly data for the 46 year period running from 1954 to 1999. We detected a small,...

The time-series approach used in the minimum wage literature essentially aims to estimate a treatment effect of increasing the minimum wage. In this paper, we employ a novel approach based on aggregate time-series data that allows us to determine if minimum wage changes have significant effects...

We introduce the package ddml for Double/Debiased Machine Learning (DDML) in Stata. Estimators of causal parameters for five different econometric models are supported, allowing for flexible estimation of causal effects of endogenous variables in settings with unknown functional forms and/or...

The widely used Oaxaca decomposition applies to linear models. Extending it to commonly used nonlinear models such as duration models is not straightforward. This paper shows that the original decomposition that uses a linear model can also be obtained by an application of the mean value...

In empirical studies it often happens that some variables for some units are far away from the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses – conclusions based on a sample with and without these...