Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling
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In honor of Dale J. Poirier, experienced editors Ivan Jeliazkov and Justin Tobias bring together a cast of expert contributors to explore the most up-to-date research on econometrics, including subjects such as panel data models, posterior simulation, and Bayesian models.

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Produktbeschreibung
In honor of Dale J. Poirier, experienced editors Ivan Jeliazkov and Justin Tobias bring together a cast of expert contributors to explore the most up-to-date research on econometrics, including subjects such as panel data models, posterior simulation, and Bayesian models.
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Autorenporträt
Ivan Jeliazkov is Associate Professor of Economics at the University of California, Irvine. He has served as Series Editor for Advances in Econometrics since 2010 and has also worked on the editorial boards of JASA/TAS Reviews and the International Journal of Mathematical Modelling and Numerical Optimisation. His research encompasses Bayesian modelling and inference, simulation-based estimation, nonparametric modelling, discrete data analysis, and model comparison. Justin Tobias is Professor and Head of the Economics Department at Purdue University. He received his PhD from the University of Chicago in 1999 and has contributed to and served as an Associate Editor for several leading econometrics journals, including the Journal of Applied Econometrics and Journal of Business and Economic Statistics. His work focuses primarily on the development and application of Bayesian microeconometric methods.