We are happy to announce the publication of our current SOEPnewsletter 107, January 2015. We have some interesting news about: SOEP data distribution soep.v30beta (what's new in the data set, data ready for sending) a note on cross-sectional weighting our plans to revise our household questionnaire news from the Cross-national Data Center in Luxembourg (LIS) some upcoming events, and some past ...
At the age of just 28, psychologist Jule Specht is an Assistant Professor at the Freie Universität Berlin and a Research Fellow at the Socio-Economic Panel (SOEP) at DIW Berlin. Jule Specht completed her undergraduate and doctoral studies in Münster. Since writing her diploma thesis, she has been studying the development of the personality across the life course using data from the SOEP. ...
The use of log-transformed data has become standard in macroeconomic forecasting with VAR models. However, its appropriateness in the context of out-of-sample forecasts has not yet been exposed to a thorough empirical investigation. With the aim of filling this void, a broad sample of VAR models is employed in a multi-country set up and approximately 42 million pseudo-out-of-sample forecasts of GDP ...
The SOEP data remain an interesting start point for research from many areas. The high number of presentations with SOEP data on national and international conferences show proof for that. On the following website you can see a composition of presentations held on basis of the SOEP data: Please click here
There is a long tradition in psychology, the social sciences and, more recently though, economics to hypothesize that religion enhances prosocial behavior. Evidence from both survey and experimental data however yield mixed results and there is barely any evidence for Germany. This study adds to this literature by exploring data from the German Socio-Economic Panel (SOEP), which provides both attitudinal ...
This paper analyses the income effect of the participation in elite sports. To quantify the average difference in the monthly net income of former elite athletes and non-athletes we estimate sample average treatment effect scores (SATT) by using covariate nearest-neighbour matching (CVM). While our treatment group consists of formerly funded top-level athletes, the control group of non-athletes is ...
