We study banks' incentive to pool assets of heterogeneous quality when investors evaluate pools by extrapolating from limited sampling. Pooling assets of heterogeneous quality induces dispersion in investors' valuations without affecting their average. Prices are determined by market clearing...

The FAMOD project, which is funded by the German Research Foundation (DFG), investigates the diversity of existing family Models after separation or divorce in Germany. The project's aim is to provide detailed information about the living conditions of mothers, fathers, and children in different...

Die Produktivität von Waldökosystemen wird durch die Bereitstellung von Nährstoffen und Wasser gewährleistet. Somit ist das Wissen über die chemischen und physikalischen Eigenschaften der Böden essentiell sowohl zur Beurteilung des Bodenzustands als auch der Güte des Waldstandorts....

Der Zensus 2022 wird in Deutschland – wie bereits der Zensus 2011 – mithilfe von registergestützten Verfahren durchgeführt. Zentrale Bedeutung, insbesondere im Hinblick auf die Ermittlung der Einwohnerzahlen der Kommunen, kommt im Zensus den Daten der Melderegister zu. Diese sind jedoch um...

We address a concern about the external validity, in particular, the representativeness of the sampled population, of an experiment conducted with university students. We do so by conducting largescale (partly) incentivized online surveys of students at a Japanese university and of a sample of...

Der Zensus 2022 wird in Deutschland - wie bereits der Zensus 2011 - mithilfe von registergestützten Verfahren durchgeführt. Zentrale Bedeutung, insbesondere im Hinblick auf die Ermittlung der Einwohnerzahlen der Kommunen, kommt im Zensus den Daten der Melderegister zu. Diese sind jedoch um...

We propose a novel view of selection bias in longitudinal surveys. Such bias may arise from initial nonresponse in a probability sample, or it may be caused by self-selection in an internet survey. A contraction theorem from mathematical demography is used to show that an initial bias can...

In this paper, we report returns to education in India using unit level data from the nationwide Periodic Labour Force Survey for 2018-19. OLS estimates from the classical Mincerian equation are presented. Various econometric techniques (e.g., conventional IV and heteroskedasticity-based IV...

This paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult...

Much of the literature on performance-related pay (PRP) and poor health relies on self-reported data, and the relationship is particularly difficult to examine due to confounding variables. To address these limitations we examine three groups of health measures using data from the UKHLS: blood...

In this paper, we report returns to education in India using unit level data from the nationwide Periodic Labour Force Survey for 2018-19. OLS estimates from the classical Mincerian equation are presented. Various econometric techniques (e.g., conventional IV and heteroskedasticity-based IV...

The microdata of surveys are valuable resources for analyzing and modeling relationships between variables of interest. These microdata are often incomplete because of nonresponses in surveys and, if not considered, may lead to model misspecification and biased results. Nonresponse variable is...

One of the areas of policy research where randomized field trials have been utilized most intensively is welfare reform. Starting in the late 1960s with experimental tests of a negative income tax and continuing through current experimental tests of recent welfare reforms, randomized evaluations...

For linear panel data models with fixed effects and sample selection, we correct for selectivity bias in the within-group estimator. The proposed procedure is equivalent to a pooled weighted least squares based on pairwise differences augmented with correction terms. A computationally affordable...

We examine the two approaches used by equity index funds to track their benchmark index. The first, full replication, mimics the index with exactness. The second, representative sampling, holds a subset of the index. We find that samplers trade 3-4 times more, have 30-50% higher expenses and...

The intensive use of acetochlor in China leads to its extensive existence in soil which may show contamination on the crop and commodities. Therefore, it is vital to assess the bioavailability and phytotoxicity of acetochlor to crops. In this study, four measurements involved in in situ pore...

The behavior of three graphene-based screen-printed electrodes (SPEs) was explored for the electroanalytical application in estradiol (E2) measurement in water samples. Characterization of the sensor was carried out using cyclic voltammetry and scanning electron microscopy. The optimal applied...

Information on water table depth (WTD) in polder areas and wetlands is important in, for example, estimating emissions of greenhouse gases, assessing the agricultural and ecological potential, and flood risk management. The seasonal variation of WTDs is summarized with averages of the yearly...

Two parallel Analog-to-Digital Converters (ADC) are the components of 2-Channel TI-ADC (for Time-Interleaved ADC). They are addressed at times nT and is the clock period). ”Timing skews” are biases of these sampling times. They vary slowly, and they have to be estimated and corrected. In...

We address a concern about the external validity, in particular, the representativeness of the sampled population, of an experiment conducted with university students. We do so by conducting large-scale (partly) incentivized online surveys of students at a Japanese university and of a sample of...

Plume chasing is cost-effective, measuring individual, on-road vehicular emissions. Whereas, wake-flow-generated turbulence results in intermittent, rapid pollutant dilution and substantial fluctuating concentrations right behind the vehicle being chased. The sampling duration is therefore one...

The necessity of detection of nitrite as a challenging compound in food industrials always has been considered. Addressed herein, two transition metal oxide based nanocatalysts, NiO ‐ Co3O4 (NC) and its reduced graphene hybridized form, NiO ‐ Co3O4 ‐ rGO (NCR), was prepared by a...

Misclassification of a binary response variable and nonrandom sample selection are data issues frequently encountered by empirical researchers. For cases in which both issues feature simultaneously in a data set, we formulate a sample selection model for a misclassified binary outcome in which...

This paper describes the weighting methodology for the second wave of the Living in Germany - Nationwide Corona Monitoring study (RKI-SOEP2). Information from the larger, ongoing German Socio-Economic Panel (SOEP) study from which the households are sampled is used to analyze the determinants of...

This paper provides details on the sampling design, fieldwork, nonresponse, and population adjustments for the 2020 sample M6 of the Socio-Economic Panel (SOEP). Sample M6 refreshes the SOEP core samples M3, M4, and M5, sampling households of refugees who arrived in Germany between January 2013...

We measure individual-level loss aversion using three incentivized, representative surveys of the U.S. population (combined N = 3,000). We find that around 50% of the U.S. population is loss tolerant, with many participants accepting negative-expected-value gambles. This is counter to earlier...

This paper studies semiparametric versions of the classical sample selection model (Heckman (1976, 1979)) without exclusion restrictions. We extend the analysis in Honor'e and Hu (2020) by allowing for parameter heterogeneity and derive implications of this model. We also consider models that...

The vast majority of empirical studies in finance employ large enough sample sizes and use the conventional thresholds for statistical significance. This routine practice can potentially lead to spurious statistically significant results. The primary aim of this paper is to present a rule of...

In recent years, semantic segmentation and classification of 3D scenes based on point cloud data have become a hot research topic. A large number of deep learning methods have been developed for point cloud. However, there are at least two problems in point cloud deep learning neural networks....

We examine the small sample properties of the GMM estimator for models of covariance structures, where the technique is often referred to as the optimal minimum distance (OMD) estimator. We present a variety of Monte Carlo experiments based on simulated data and on the data used by Abowd and...