Infra-monthly time series have increasingly appeared on the radar of official statistics in recent years, mostly as a consequence of a general digital transformation process and the outbreak of the COVID-19 pandemic in 2020. Many of those series are seasonal and thus in need for seasonal...

Large-scale environmental programs generally commit substantial societal resources, making the evaluation of their actual effects on the relevant outcomes imperative. As the example of the subsidization of energy-saving appliances illustrates, much of the applied environmental economics...

Infra-monthly economic time series have become increasingly popular in official statistics in recent years. This evolution has been largely fostered by official statistics’ digital transformation during the last decade. The COVID-19 pandemic outbreak in 2020 has added fuel to the fire as many...

The COVID-19 outbreak in 2020 has fostered in many countries the development of new weekly economic indices for the timely tracking of pandemic-related turmoils and other forms of rapid economic changes. Such indices often utilise information from daily and weekly economic time series that...

We consider the problem of regressions with selectively observed covariates in a nonparametric framework. Our approach relies on instrumental variables that explain variation in the latent covariates but have no direct e ffect on selection. The regression function of interest is shown to be a...

We present a new method for imposing and testing concavity of a cost function using asymptotic least squares, which can easily be implemented even for cost functions which are nonlinear in parameters. We provide an illustration on the basis of a (generalized) Box-Cox cost function with six...

In this paper we analyze the effects of a German job creation scheme (JCS) on the social integration and well-being of long-term unemployed individuals. Using linked survey and administrative data for participants and a group of matched non-participants, we find significant positive effects of...

We develop a new Bayesian estimator that is able to deal with multivariate panel data structure in the presence of spatial correlation. The analysis of panel data introduced here allows us to analyze not only the fixed effect but also the random effect model. This work extends the previous study...