Trust between individuals and groups: Groups are less trusting than individuals but just as trustworthy

We compare the behavior of groups and individuals in a two-person trust game. The first mover in this game, the sender, receives an endowment and can send any part of it to the responder; the amount sent is tripled, and the responder can then return to the sender any portion of the tripled sum. In a 2 × 2 design, the players in the roles of sender and responder are either individuals or groups of three players (who conduct face-to-face discussions to decide on a collective group strategy). We find that groups in the role of sender send smaller amounts than individuals, and expect lower returns. In particular, groups send nothing more often than individuals do (and are even more likely to do so when the responder is another group). Groups and individuals in the role of responder return on average the same fraction of the amount sent. Hence, we conclude that groups are less trusting than individuals, but just as trustworthy.     

Auswirkungen Der Familiengründung Auf Den Berufsverlauf Von Männern

In this article we use longitudinal data from the German socio-economic Panel to examine the relationship between parenthood and labour market outcomes for men. Both traditional sociological and economical perspectives predict a positive effect of fatherhood on wages, whereas the spreading idea of a modern fatherhood suggests that, at least, fathers of the younger generation tend to reduce their working hours and thus accept wage reductions. Our focus is on the effect of fatherhood on wage growth, hours worked and interfirm mobility. We find that fathers receive higher wages than married men without children, even when controlling for selection into fatherhood. The positive income effect of fatherhood results from greater on-the-job wage growth. However, fathers are not likely to increase their wage by working longer hours or leaving their current employer for a better paid position.     

A Tail Quantile Approximation for the Student t Distribution

In this article, we derive a new formula for extreme Student t quantiles. We use the fact that the Student t distribution arises as the limit of a variance-mixture of normals. For the normal distribution there is already a tail quantile formula derived by Reiss (1989 Reiss , R.-D. ( 1989 ). Approximate Distributions of Order Statistics: With Applications to Non-parametric Statistics . New York : Springer .[Crossref] , [Google Scholar]). We generalize his procedure and transfer it to our scenario.

Eventually, we compare the quantile estimates of our formula to those from Gafer and Kafadar (1984 Gafer , D. P. , Kafadar , K. ( 1984 ). A retrievable recipe for inverse t. Amer. Statistician 38(4):308–311 . [Google Scholar]), who also derived a Student t quantile formula. Using R to generate a benchmark we find that our method is more accurate for very high quantiles.     

On Robustness of Model-Based Bootstrap Schemes in Nonparametric Time Series Analysis

Theory in time series analysis is often developed under the assumption of finite-dimensional models for the data generating process. Whereas corresponding estimators such as those of a conditional mean function are reasonable even if the true dependence mechanism is more complex, it is usually necessary to capture the whole dependence structure asymptotically for the bootstrap to be valid. In contrast, we show that certain simplified bootstrap schemes which imitate only some aspects of the time series are consistent for quantities arising in nonparametric statistics. To this end, we generalize the well-known "whitening by windowing" principle to joint distributions of nonparametric estimators of the autoregression function. Consequently, we obtain that model-based nonparametric bootstrap schemes remain valid for supremum-type functionals as long as they mimic those finite-dimensional joint distributions consistently which determine the quantity of interest. As an application, we show that simple regression-type bootstrap schemes can be applied for the determination of critical values for nonparametric tests of parametric or semiparametric hypotheses on the autoregression function in the context of a general process.     

How Long Is a Spell of Unemployment? Illusions and Biases in the Use of CPS Data

Most data used to study the durations of unemployment spells come from the Current Population Survey (CPS), which is a point-in-time survey and gives an incomplete picture of the underlying duration distribution. We introduce a new sample of completed unemployment spells obtained from panel data and apply CPS sampling and reporting techniques to replicate the type of data used by other researchers. Predicted duration distributions derived from this CPS-like data are then compared to the actual distribution. We conclude that the best inferences that can be made about unemployment durations by using CPS-like data are seriously biased.     

The instability of robust aggregation

Levis robust aggregation suggests a generalization of the standard ex ante mode of aggregating individuals expected utilities into a social choice function. This generalization applies some social choice rule not only to the actual individuals but also to hypothetical individuals with all possible combinations of the actual individuals probabilities and utilities. We show that robust aggregation can lead to preference reversals in the social choice when the very same decision situation is described with different degrees of detail, thus violating a desirable stability condition. We also show that any stable robust social choice rule must collapse back into the ex ante mode without recourse to hypothetical individuals. Under sufficient conditions, such as strong Pareto optimality, robust aggregation even leads to an infinite series of reversals in group choices. By contrast, stability is ubiquitous in the standard ex ante mode and is closely related to independence of irrelevant alternatives.I wish to thank Christs College, Cambridge and the California Institute of Technology for their generous financial and academic support. I am grateful to three anonymous referees for their helpful comments. I am much indebted to Isaac Levi, Philippe Mongin and Teddy Seidenfeld for their help and encouragement.