CALL FOR PAPERS
3ed Special Issue on BAYESIAN METHODS IN STATISTICS AND ECONOMETRICS

Econometrics and Statistics
http://www.elsevier.com/locate/ecosta

We are inviting submissions for a special issue of the journal
Econometrics and Statistics focused on Bayesian methods in statistics
and econometrics.

We are particularly interested in manuscripts that develop, illustrate
and showcase innovative Bayesian approaches in a broad domain area,
e.g., in astronomy, environmental studies, biology, medicine,
neurosciences, finance, economics, business and industry. In
particular, Bayesian econometrics has a specifically dedicated section
within this special issue. Contributions that contain significant
developments in causal inference, (broadly defined) nonparametric
methods, variable selection, and computationally efficient approaches
to handling big data, are encouraged.

In order to be considered for publication the papers should have a
significant novel Bayesian component. Original methodological
contributions inspired by specific applications are of particular
interest. Papers dealing, directly or indirectly, with theoretical,
computational and technical elements are also welcome. Papers that
apply known techniques to a range of models and/or data are generally
discouraged. Authors who are uncertain about the suitability of their
papers should contact the editors. All submissions must contain
original unpublished work that is not being considered for publication
elsewhere.

Submissions will be refereed according to standard procedures for
Econometrics and Statistics. Information about the journal can be
found at http://www.elsevier.com/locate/ecosta.

The deadline for submissions is 31 December 2023.  However, papers can
be submitted at any time and once they are received, they will enter
the editorial system immediately.

Papers for the special issue should be submitted using the Elsevier
Electronic Submission tool EM:
https://www.editorialmanager.com/ecosta/.
In the EM, please choose the special issue on Bayesian methods in
econometrics and statistics.

The special issue editors:

Roberto Casarin, University Ca' Foscari of Venice
Email: r.casarin@unive.it

Luciana DallaValle, University of Plymouth, UK
Email: luciana.dallavalle@plymouth.ac.uk

Michele Guindani, University of California, Los Angeles, USA.
Email: Mguindani@ucla.edu

Daniel Kowal, Rice University, USA
Email: daniel.kowal@rice.edu

Yasuhiro Omori, University of Tokyo, Japan.
E-mail: omori@e.u-tokyo.ac.jp