★ Econometrics (ISSN 2225-1146)
★ Special Issue "Discrete-Valued Time Series: Modelling, Estimation and Forecasting"
★ https://www.mdpi.com/journal/econometrics/special_issues/count_data


★ Call for papers

Dear Colleagues,

This Special Issue is concerned with publishing a range of new contributions to the field of Discrete-Valued Time Series. Both methodological advances and applications are encouraged; papers which combine the two are particularly sought. Contributions may involve univariate and, particularly, multivariate time series models; these may be either observation- or parameter-driven. Topics include specification and estimation, as well as inference methods.

Count time series are usually non-negative integers, but papers dealing with binary and categorical variables are also welcome. Methodology may be classical or Bayesian in nature. There is, as of yet, a limited literature on goodness-of-fit methods in this area of modelling and so we would welcome contributions in this field. Other ripe topics for advancement would include forecasting and its applications, change-point detection and diagnostic and model testing methods. General dynamic analysis including impulse response analysis would also be of interest.

The Special Issue seeks to bring together a burgeoning stream of literature across a range of fields including, but not limited to, medicine; epidemiology; finance; and economics, discussing advances.

Overall, the main thrust of the Special Issue is to develop and refine extant methods for analysis of count time series data and to advance knowledge and applicability in novel and exciting directions.

Prof. Brendan McCabe
Prof. Andrew R. Tremayne
University of Liverpool
Guest Editors

★ Submissions deadline: 31 December 2020
★ Submission Instructions: https://www.mdpi.com/journal/econometrics/instructions


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** Rapid Publication: Manuscripts are peer-reviewed and a first decision provided to authors approximately 38.2 days after submission; acceptance to publication is undertaken in 7.8 days (median values for papers published in this journal in the first half of 2020).

★ Open Access and Article Processing Charges (APC):

Econometrics is fully open access. Open access (unlimited and free access by readers) increases publicity and promotes more frequent citations, as indicated by several studies. Open access is supported by the authors and their institutes. The Article Processing Charges (APC) for accepted papers are CHF 1000. You may be entitled to a discount if you have previously received a discount code in MDPI or if your institute is participating in the MDPI Institutional Open Access Program (IOAP), for more information see: http://www.mdpi.com/about/ioap.

Discounts/Waivers could be granted for strong papers. Feel free to contact the editorial office.


★ Contact:

Econometrics Editorial Office
MDPI, St. Alban-Anlage 66, 4052 Basel, Switzerland
Email: econometrics@mdpi.com

Ms. Jade Wei
Managing Editor
Email: jade.wei@mdpi.com