This paper provides details on the sampling design, field results and nonresponse, as well as population adjustments for the 2018 Sample O of the Socio-Economic Panel (SOEP). Sample O refreshes the SOEPCore sample by adding the residents of households in neighborhoods that receive government...

Dieses Papier stellt das Stichprobendesign, Ergebnisse der Feldarbeit, Analysen zur Selektivität sowie Informationen zur Randanpassung der Studie Sozio-ökonomische Faktoren und Folgen der Verbreitung des Coronavirus in Deutschland vor. Die Stichprobe setzt sich aus einer zufälligen Auswahl...

This paper provides details on the sampling design, field results and nonresponse, as well as population adjustments for the 2018 Sample O of the Socio-Economic Panel (SOEP). Sample O refreshes the SOEPCore sample by adding the residents of households in neighborhoods that receive government...

We consider a situation where the sample design of a survey is modified over time in order to save resources. The former design is a classical large-scale survey. The new design is a mixed mode survey where a smaller classical sample is augmented by records of an online survey. For the online...

We investigate identification of causal parameters in case-control and related studies. The odds ratio in the sample is our main estimand of interest and we articulate its relationship with causal parameters under various scenarios. It turns out that the odds ratio is generally a sharp upper...

We examine the performance of asymptotic inference as well as bootstrap tests for the Alphabeta and Kobus-Miłoś family of inequality indices for ordered response data. We use Monte Carlo experiments to compare the empirical size and statistical power of asymptotic inference and the Studentized...

Empirical Best Predictors (EBPs) are widely used for small area estimation purposes. In the case of longitudinal surveys, this class of predictors can be used to predict any given population or subpopulation characteristic for any time period, including future periods. Generally, the value of an...

Dieses Papier stellt das Stichprobendesign, Ergebnisse der Feldarbeit, Analysen zur Selektivität sowie Informationen zur Randanpassung der Studie Sozio-ökonomische Faktoren und Folgen der Verbreitung des Coronavirus in Deutschland vor. Die Stichprobe setzt sich aus einer zufälligen Auswahl...

A novel approach to inference for a specific region of the predictive distribution is introduced. An important domain of application is accurate prediction of financial risk measures, where the area of interest is the left tail of the predictive density of logreturns. Our proposed approach...

The beta coefficient plays a crucial role in finance as a risk measure of a portfolio in comparison to the benchmark portfolio. In the paper, we investigate statistical properties of the sample estimator for the beta coefficient. Assuming that both the holding portfolio and the benchmark...

Using a case study approach, this research explores the various potential limiting factors of climate change adaptation, based on the experience of four low-lying islands in central Philippines. In the aftermath of the 2013 7.2-magnitude Bohol earthquake, the islands now become flooded even...

The paper discusses methodological topics of bankruptcy prediction modelling—unbalanced sampling, sample bias, and unbiased predictions of bankruptcy. Bankruptcy models are typically estimated with the use of non-random samples, which creates sample choice biases. We consider two types of...

This paper studies inference in randomized controlled trials with covariate-adaptive randomization when there are multiple treatments. More specifically, we study in this setting inference about the average effect of one or more treatments relative to other treatments or a control. As in Bugni...

We present a general framework for studying regularized estimators; such estimators are pervasive in estimation problems wherein \plug-in" type estimators are either ill-defined or ill-behaved. Within this framework, we derive, under primitive conditions, consistency and a generalization of the...

In a randomized control trial, the precision of an average treatment effect estimator and the power of the corresponding t-test can be improved either by collecting data on additional individuals, or by collecting additional covariates that predict the outcome variable. To design the...

A novel approach to inference for a specific region of the predictive distribution is introduced. An important domain of application is accurate prediction of financial risk measures, where the area of interest is the left tail of the predictive density of logreturns. Our proposed approach...

This paper studies inference in randomized controlled trials with covariate‐adaptive randomization when there are multiple treatments. More specifically, we study in this setting inference about the average effect of one or more treatments relative to other treatments or a control. As in...

We consider identification and estimation of nonseparable sample selection models with censored selection rules. We employ a control function approach and discuss different objects of interest based on (1) local effects conditional on the control function, and (2) global effects obtained from...

We develop a distribution regression model under endogenous sample selection. This model is a semiparametric generalization of the Heckman selection model that accommodates much rich patterns of heterogeneity in the selection process and effect of the covariates. The model applies to continuous,...

There is potential for measurement problems in both retrospective and panel microdata. In this paper, we compare results on basic indicators related to labor markets and their dynamics from retrospective and panel survey data in Egypt, in order to determine the conditions under which results are...

We study the impact of manipulating the attention of a decision-maker who learns sequentially about a number of items before making a choice. Under natural assumptions on the decision-maker's strategy, forcing attention toward one item increases its likelihood of being chosen.

Studying the likelihood that individuals cheat requires a valid statistical measure of dishonesty. We develop an easy empirical method to measure and compare lying behavior within and across studies to correct for sampling errors. This method estimates the full distribution of lying when agents...

Accounting for sample selection is a challenge not only for empirical researchers, but also for the agents populating our models. Yet most models abstract from these issues and assume that agents successfully tackle selection problems. We design an experiment where a person who understands...

Indirect inference testing can be carried out with a variety of auxiliary models. Asymptotically these different models make no difference. However, the small sample properties can differ. We explore small sample power and estimation bias both with different variable combinations and descriptive...

Econometric analysis requires filtering techniques that are adapted to cater to data sequences that are short and that have strong trends. Whereas the economists have tended to conduct their analyses in the time domain, the engineers have emphasised the frequency domain. This paper places its...

Pseudo-panels allow estimation of panel models when only repeated cross-sections are available. This involves grouping individuals into cohorts and using the cohort means as if they are observations in a genuine panel. Their practical use is constrained by a lack of consensus on how the...

We consider identification and estimation of nonseparable sample selection models with censored selection rules. We employ a control function approach and discuss different objects of interest based on (1) local effects conditional on the control function, and (2) global effects obtained from...