Topic Survey Methodology and Data-Science

SOEPcampus@European University Viadrina

This 1/2 day workshop offers a first and practically oriented introduction into the sophisticated data source of the SOEP. Participants will be introduced to the content of the study, its data-structure, sample selection and weighting strategy and they will be provided with an overview over the study documentation. Additionally we will discuss the specific potentials for longitudinal data analyses...

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...

Policy Evaluation of Waste Pricing Programs Using Heterogeneous Causal Effect Estimation

Using machine learning methods in a quasi-experimental setting, I study the heterogeneous effects of introducing waste prices - unit prices on household unsorted waste disposal - on waste demands and municipal costs. Using a unique panel of Italian municipalities with large variation in prices and observables, I show that waste demands are nonlinear. I find evidence of constant elasticities at low ...

An Alternative Bootstrap for Proxy Vector Autoregressions

We propose a new bootstrap algorithm for inference for impulse responses in structural vector autoregressive models identified with an external proxy variable. Simulations show that the new bootstrap algorithm provides confidence intervals for impulse responses which often have more precise coverage than and similar length to the competing moving-block bootstrap intervals. An empirical example shows ...

Multiple Imputation of Ordinal Missing Not at Random Data

We introduce a selection model-based imputation approach to be used within the Fully Conditional Specification (FCS) framework for the Multiple Imputation (MI) of incomplete ordinal variables that are supposed to be Missing Not at Random (MNAR). Thereby, we generalise previous work on this topic which involved binary single-level and multilevel data to ordinal variables. We apply an ordered probit ...

The Early Bird Catches the Worm! Setting a Deadline for Online Panel Recruitment Incentives

The literature on the effects of incentives in survey research is vast and covers a diversity of survey modes. The mode of probability-based online panels, however, is still young and so is research into how to best recruit sample units into the panel. This paper sheds light on the effectiveness of a specific type of incentive in this context: a monetary incentive that is paid conditionally upon panel ...

Monetary Policy, External Instruments, and Heteroskedasticity

We develop a structural vector autoregressive framework that combines external instruments and heteroskedasticity for identification of monetary policy shocks. We show that exploiting both types of information sharpens structural inference, allows testing the relevance and exogeneity condition for instruments separately using likelihood ratio tests, and facilitates the economic interpretation of the ...

Do Rent Controls and Other Tenancy Regulations Affect New Construction? Some Answers from Long-Run Historical Evidence

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 ...

How Communication Makes the Difference between a Cartel and Tacit Collusion: A Machine Learning Approach

This paper sheds new light on the role of communication for cartel formation. Using machine learning to evaluate free-form chat communication among firms in a laboratory experiment, we identify typical communication patterns for both explicit cartel formation and indirect attempts to collude tacitly. We document that firms are less likely to communicate explicitly about price fixing and more likely ...