Codebook and documentation of the panel study 'Labour Market and Social Security' (PASS) : vol. 1: Introduction and overview, wave 1 (2006/2007)

"The panel study 'Labour Market and Social Security' (PASS), established by the Institute for Employment Research (IAB), is a new dataset for labour market, welfare state and poverty research in Germany, creating a new empirical basis for the scientific community and political consulting. This Datenreport provides an overview of the first survey wave, for which 18,954 persons were interviewed in 12,794 households between December 2006 and July 2007. The study is carried out as part of the IAB's research into the German Social Code Book II (SGB II). The IAB is charged by law with studying the effects of benefits under SGB II for integration into the labour market and subsistence benefits. However, due to the complex sample design, it also enables researchers to answer questions far beyond these issues. Five core questions influenced the development of the new study, which are detailed in Achatz et al. (2007): 1. What options exist to regain independence from Unemployment Benefit II? 2. In which ways does the social situation of a household change when it receives benefits? 3. How do persons concerned cope with their situation? Will attitudes of the respondents that are constitutive for their actions change over time? 4. In which form do contacts between benefit recipients and institutions providing basic social security actually take place? What are the institutional procedures applied in practice? 5. Which employment career patterns or household dynamics lead to receipt of Unemployment Benefit II? The following brief overview describes the motivation for carrying out the survey, its contents and the study design." (text excerpt, IAB-Doku) ((en)) Additional Information Questionnaires of the first wave. Here you can find the German version. Further information about the panel study "Labour Market and Social Security"IAB-Haushaltspanel, Datengewinnung, Erhebungsmethode, Stichprobe, Panel - Methode, Datenaufbereitung

MARLUI: Multi-Agent Reinforcement Learning for Adaptive UIs

Adaptive user interfaces (UIs) automatically change an interface to better support users' tasks. Recently, machine learning techniques have enabled the transition to more powerful and complex adaptive UIs. However, a core challenge for adaptive user interfaces is the reliance on high-quality user data that has to be collected offline for each task. We formulate UI adaptation as a multi-agent reinforcement learning problem to overcome this challenge. In our formulation, a user agent mimics a real user and learns to interact with a UI. Simultaneously, an interface agent learns UI adaptations to maximize the user agent's performance. The interface agent learns the task structure from the user agent's behavior and, based on that, can support the user agent in completing its task. Our method produces adaptation policies that are learned in simulation only and, therefore, does not need real user data. Our experiments show that learned policies generalize to real users and achieve on par performance with data-driven supervised learning baselines

Design and stratification of PASS: a new panel study for research on long term unemployment

"Dieses Discussion Paper stellt Design und Besonderheiten der Panelstudie PASS vor. PASS ist im Rahmen der SGB-II-Forschung im IAB angesiedelt und kombiniert eine Zufallsstichprobe von 6.000 Haushalten, die Leistungen nach dem SGB II erhalten, mit einer ebenso großen Stichprobe der allgemeinen Bevölkerung. Dieses Design ermöglicht die Beantwortung einer Vielzahl von Fragestellungen der Arbeitsmarkt-, Armuts- und Sozialstaatsforschung. Im Ergebnisteil analysieren wir die Auswirkungen der Schichtung der Bevölkerungsstichprobe nach dem Statusindex eines kommerziellen Anbieters." (Autorenreferat)"The paper introduces the general design features and particularities of a new largescale panel study for research on recipients of benefits for the long-term unemployed (the so called Unemployment Benefit II) in Germany that combines a sample of 6000 recipient households with an equally large sample of the general population. Particular focus is on the sampling procedure for the general population, where a commercial database was used to draw a sample stratified by status." (author's abstract