Regression‐type models for extremal dependence

We propose a vector generalized additive modeling framework for taking into account the effect of covariates on angular density functions in a multivariate extreme value context. The proposed methods are tailored for settings where the dependence between extreme values may change according to covariates. We devise a maximum penalized log‐likelihood estimator, discuss details of the estimation procedure, and derive its consistency and asymptotic normality. The simulation study suggests that the proposed methods perform well in a wealth of simulation scenarios by accurately recovering the true covariate‐adjusted angular density. Our empirical analysis reveals relevant dynamics of the dependence between extreme air temperatures in two alpine resorts during the winter season.     

Non-minimization of source taxes on labor income: empirical evidence from Germany

The present paper analyzes the choice of tax classes by married couples under the German withholding tax on wage income. Making use of micro data from official tax returns for the year 1998 and conducting simulation analysis, it is shown that more than 20 percent of the observed households do not choose the tax class combination that minimizes withholding. In the second part of the paper, several explanations for this result are discussed. Among those explanations, transaction costs and Pareto-inefficient intrahousehold-decision-making are the most likely.     

Negotiating the Unknown: The Role of Uncertainty in Social Exchange

This article documents the role of uncertainty in social exchange. Specifically, it reviews how social exchange theorists incorporate uncertainty when explaining psychological processes and social behaviors. After identifying and examining the structural roots of uncertainty, the article addresses how uncertainty affects actor behavior and attitude formation, from curbing power use to promoting the development of more committed, trusting and cohesive exchange partnerships. By assessing the consequences of uncertainty and risk for social exchange, this article contributes to sociological knowledge about the nature and form of relationships in an uncertain world.     

Inference based on conditional speclfication

The first bibliography in the area of inference based on conditional specification was published in 1977, A second bibliography is compiled, and a combined subject index is given.     

Testing goodness of fit via nonparametric function estimation techniques

An overview is given of methodology for testing goodness of fit of parametric models using nonparametric function estimation techniques. The ideas are illustrated in two settings: the classical one-sample goodness-of-fit scenario and testing the goodness of fit of a polynomial regression model.     

A genetic algorithm for assembly line balancing

Assembly line balancing is a very important aspect in any mass production setup. However, finding the optimal balance is a very difficult proposition because of the computational complexity involved. Hence sub-optimal solutions are preferred over optimal solutions. In this work, a genetic algorithm (GA) is presented for obtaining good quality solutions for assembly line balancing problems. A major feature of GA is the ability to take care of a variety of objective functions. A modified GA working with two populations, one of which allows infeasible solutions, and exchange of specimens at regular intervals is proposed for handling irregular search spaces. The experimental results obtained with a single population, as well as two populations are encouraging.