Topic Survey Methodology and Data-Science

A Tale of Two Data Sets: Comparing German Administrative and Survey Data Using Wage Inequality as an Example

The IAB’s Sample of Integrated Labour Market Biographies (SIAB) and the Socio-Economic Panel (SOEP) are the two data sets most commonly used to analyze wage inequality in Germany. While the SIAB is based on administrative reports by employers to the social security system, the SOEP is a survey data set in which respondents self-report their wages. Both data sources have their specific advantages and ...

The Effectiveness of FX Interventions: A Meta-Analysis

There is ample empirical literature centering on the effectiveness of foreign exchange intervention (FXI). Given the mix of objectives and country-heterogeneity, the general lack of consensus thus far is no surprise. We shed light on this debate by conducting the first comprehensive meta-analysis in the FXI literature, with 279 reported effects that stem from 74 distinct empirical studies. We cover ...

SOEPcampus after Work -

The German Socio-Economic Panel Study is a representative panel study for the German population, collecting data on a broad variety of topics of everyday life, including general wellbeing, household composition, educational aspirations and educational status, income and occupational biographies, leisure time activities, housing, health, political orientation and more. With its long running panel...

Learn to use the SOEP over Lunch

The German Socio-Economic Panel Study is a representative panel study for the German population, collecting data on a broad variety of topics of everyday life, including general wellbeing, household composition, educational aspirations and educational status, income and occupational biographies, leisure time activities, housing, health, political orientation and more. With its long running panel...

SOEPcampus@Home

The German Socio-Economic Panel Study is a representative panel study for the German population, collecting data on a broad variety of topics of everyday life, including general wellbeing, household composition, educational aspirations and educational status, income and occupational biographies, leisure time activities, housing, health, political orientation and more. With its long running panel...

Linked Open Research Data for Social Science Pilot Study (LORDpilot)

The re-use of research data is an integral part of research practice in the social and economic sciences. To find relevant data, researchers need adequate search facilities. However, a comprehensive, thematic search for research data that is not limited to individual survey programs is difficult. Because individual survey programs use their own terminology to describe their data and the...

Macroeconometric Workshop

We are pleased to announce that on May 27, 2022 DIW Berlin will host the “Macroeconometric Workshop”. The workshop covers presentations of both methodological and applied contributions on the frontier of research in quantitative macroeconomics, with a focus on empirical research. The event is jointly organized by the School of Business & Economics of Freie Universität Berlin...

SOEP-IS for new research questions: call for proposals for the 2023 survey

Researchers in Germany and abroad are invited to submit proposals for the next round of the SOEP Innovation Sample (SOEP-IS). For those not yet familiar with SOEP-IS, this unique random sample of German households (N = 2,800 households with about 4,000 respondents) offers great potential as a source of household micro-data, particularly for researchers seeking information that is not available in SOEP-Core—for ...

SOEPcampus@Home

The German Socio-Economic Panel Study is a representative panel study for the German population, collecting data on a broad variety of topics of everyday life, including general wellbeing, household composition, educational aspirations and educational status, income and occupational biographies, leisure time activities, housing, health, political orientation and more. With its long running panel...

Unsupervised Methods: Clustering Methods