Special Issue "Advances in Econometric Analysis and Its Applications"

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Mathematical Finance".

Deadline for manuscript submissions: 31 July 2020.

Special Issue Editor

Prof. Dr. Mike Tsionas
Website
Guest Editor
Lancaster University Management School, LA1 4YX, United Kingdom
Interests: Econometrics, Applied econometrics, Bayesian techniques in time series and panel data, Efficiency and productivity and Banking models

Special Issue Information

Dear Colleagues,

The purpose of the Special Issue of JRFM is to provide new perspectives, models, and applications in econometrics. Summaries of relatively recent econometric techniques, useful for practitioners, are also welcome. Theoretical and empirical contributions are also welcome, provided there is a novel element or a review of novel techniques that have been published in major journals but whose application is still limited in practice.

You are more than welcome to send your contribution for consideration.

Prof. Dr. Mike Tsionas
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 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. 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. Journal of Risk and Financial Management is an international peer-reviewed open access monthly 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 1000 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

  • Econometrics
  • Applied econometrics
  • Time series analysis
  • Panel data
  • Econometric theory

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?
J. Risk Financial Manag. 2020, 13(3), 44; https://doi.org/10.3390/jrfm13030044 - 02 Mar 2020
Abstract
Professional forecasters can rely on an econometric model to create their forecasts. It is usually unknown to what extent they adjust an econometric model-based forecast. In this paper we show, while making just two simple assumptions, that it is possible to estimate the [...] Read more.
Professional forecasters can rely on an econometric model to create their forecasts. It is usually unknown to what extent they adjust an econometric model-based forecast. In this paper we show, while making just two simple assumptions, that it is possible to estimate the persistence and variance of the deviation of their forecasts from forecasts from an econometric model. A key feature of the data that facilitates our estimates is that we have forecast updates for the same forecast target. An illustration to consensus forecasters who give forecasts for GDP growth, inflation and unemployment for a range of countries and years suggests that the more a forecaster deviates from a prediction from an econometric model, the less accurate are the forecasts. Full article
(This article belongs to the Special Issue Advances in Econometric Analysis and Its Applications)
Open AccessArticle
Robust Bayesian Inference in Stochastic Frontier Models
J. Risk Financial Manag. 2019, 12(4), 183; https://doi.org/10.3390/jrfm12040183 - 04 Dec 2019
Abstract
We use the concept of coarsened posteriors to provide robust Bayesian inference via coarsening in order to robustify posteriors arising from stochastic frontier models. These posteriors arise from tempered versions of the likelihood when at most a pre-specified amount of data is used, [...] Read more.
We use the concept of coarsened posteriors to provide robust Bayesian inference via coarsening in order to robustify posteriors arising from stochastic frontier models. These posteriors arise from tempered versions of the likelihood when at most a pre-specified amount of data is used, and are robust to changes in the model. Specifically, we examine robustness to changes in the distribution of the composed error in the stochastic frontier model (SFM). Moreover, coarsening is a form of regularization, reduces overfitting and makes inferences less sensitive to model choice. The new techniques are illustrated using artificial data as well as in a substantive application to large U.S. banks. Full article
(This article belongs to the Special Issue Advances in Econometric Analysis and Its Applications)
Show Figures

Figure 1

Back to TopTop