Innovations in Bayesian Econometrics: Theory, Techniques, and Economic Analysis
A special issue of Econometrics (ISSN 2225-1146).
Deadline for manuscript submissions: 31 May 2025 | Viewed by 179
Special Issue Editor
Special Issue Information
Dear Colleagues,
In recent years, ongoing innovations in Bayesian econometric theories and estimation techniques have demonstrated the substantial advantages of Bayesian econometrics over other methods. In this context, this Special Issue seeks to present a carefully curated selection of research articles that exemplify these advancements in a timely manner.
Both theoretical papers and applied works addressing important economic and financial issues are welcome. Areas of Bayesian analysis may include (but are not limited to) the following:
- Cluster analysis;
- Density forecasting;
- Distribution theory;
- Factor models;
- Global–local shrinkage;
- Graphical models;
- Machine learning;
- Mixed-frequency methods;
- Mixture models;
- Model averaging and selection;
- Multivariate analysis;
- Network models;
- Non- and semiparametric inferences;
- Optimization;
- Quantile regression;
- Spatial models;
- State-space models;
- Tensor analysis;
- Uncertainty quantification;
- Variable selection.
I look forward to receiving your original contributions.
Dr. Deborah Gefang
Guest Editor
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 submissions that pass pre-check are 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. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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 Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- non- and semiparametric inferences
- mixture models
- vector autoregressions
- quantile regression
- mixed-frequency methods
- state-space models
- forecasting
- parameter shrinkage and variable selection
- uncertainty
- machine learning
