Special Issue "Bayesian and Frequentist Model Averaging"
A special issue of Econometrics (ISSN 2225-1146).
Deadline for manuscript submissions: closed (30 September 2019) | Viewed by 39268
Interests: theoretical and applied Bayesian statistics, particularly distribution theory, Bayesian model averaging, spatial statistics, non- and semiparametric inference, survival models, stochastic frontier models.
Interests: econometric theory; model averaging; risk; environmental economics; matrix calculus
Interests: statistical analysis of computer models; model uncertainty; model and variable selection; objective Bayesian methods
This Special Issue aims at gathering original contributions on model averaging methods and their applications in econometrics. We focus on model averaging as a response to model uncertainty, which is an inherent aspect of modelling. The weights used for averaging are often derived from Bayes theorem (Bayesian model averaging) or from sampling-theoretic optimality considerations (frequentist model averaging). We will also consider methods that combine aspects of both frequentist and Bayesian reasoning, such as weighted average least squares. We would like to invite you to submit papers in this general area that make contributions of a methodological or applied nature, or both, especially (but not necessarily) in settings that extend the more or less well-understood normal linear regression model. Papers that deal with the computational issues induced by very large model spaces and/or complex model structures are also welcomed. Papers that create additional insight by comparing various methodologies in challenging and relevant settings could also be of interest.
Over the last two decades, model averaging has become an increasingly popular approach to dealing with model uncertainty in economics, and we believe this Special Issue can make an important contribution to firmly establishing the methodologies based on model averaging as an important and well-understood part of the standard econometrics toolbox.
Prof. Dr. Mark F.J. Steel
Prof. Dr. Jan R. Magnus
Prof. Dr. Gonzalo García-Donato
Prof. Dr. Xinyu Zhang
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. For this Special Issue, we particularly invite research articles, but do not entirely exclude review articles and short communications.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Econometrics is an international peer-reviewed open access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charges do not apply for this Special Issue, resulting in no charge to authors. Submitted papers should preferably be prepared in LaTeX, and written in (standard academic) high-level English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Model averaging
- Model uncertainty
- Bayesian model averaging
- Frequentist model averaging
- Weighted average least squares
- Markov chain Monte Carlo methods