Logistic regression is a very popular binary classification technique in many industries, particularly in the financial service industry. It has been used to build credit scorecards, estimate the probability of default or churn, identify the next best product in marketing, and many more...

The multinomial logit model with random coefficients is widely used in applied research. This paper is concerned with estimating a random coefficients logit model in which the distribution of each coefficient is characterized by finitely many parameters. Some of these parameters may be zero. The...

Spatial dynamic microsimulations allow for the multivariate analysis of complex socioeconomic systems with geographic segmentation. For this, a synthetic replica of the system as base population is stochastically projected into future periods. Thereby, the projection is based on micro-level...

Regression models for proportions are frequently encountered in applied work. The conditional expectation is bound between 0 and 1 and, therefore, must be non-linear which requires non-standard panel data extensions. The quasi-maximum likelihood estimator of Papke and Wooldridge (1996) suffers...

Traffic congestion contributes to longer travel times and increased travel time variability. We account for the dynamic nature of travellers' choices, by deriving a closed-form solution for the costs of travel time variability. The resulting travel delay cost function is linear in the mean...