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Rainer Winkelmann

Researcher at University of Zurich

Publications -  172
Citations -  9608

Rainer Winkelmann is an academic researcher from University of Zurich. The author has contributed to research in topics: Count data & Unemployment. The author has an hindex of 46, co-authored 169 publications receiving 9130 citations. Previous affiliations of Rainer Winkelmann include Ludwig Maximilian University of Munich & Institute for the Study of Labor.

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Journal ArticleDOI

Why Are the Unemployed So Unhappy? Evidence from Panel Data

TL;DR: In this article, the importance of non-pecuniary costs of unemployment using a longitudinal data-set on life-satisfaction of working-age men in Germany was tested.
Book

Econometric Analysis of Count Data

TL;DR: A survey of statistical and econometric techniques for the analysis of count data, with a focus on conditional distribution models, can be found in this paper, where the authors provide an up-to-date survey.
Posted Content

Consistent Estimation of the Fixed Effects Ordered Logit Model

TL;DR: In this article, the authors re-examine existing estimators for the panel data fixed effects ordered logit model, and propose a new one, and study the sampling properties of these estimators in a series of Monte Carlo simulations.
Journal ArticleDOI

Recent developments in count data modelling: theory and application

TL;DR: In this paper, statistical methods for modeling individual behavior when the endogenous variable is a nonnegative integer are discussed with a focus on specification, estimation, and testing, and an application to labor mobility data illustrates the gain obtained by carefully taking into account the specific structure of the data.
Posted Content

The Trade Effects of Endogenous Preferential Trade Agreements

TL;DR: In this article, an empirical model that takes into account both that preferential trade agreement membership is endogenous and that the world matrix of bilateral trade flows contains numerous zero entries is presented, which is treated in an encompassing way by means of (possibly two-part) Poisson pseudo-maximum likelihood estimation with endogenous binary indicator variables in the empirical model.