0169-2070
Published by: Elsevier
https://www.journals.elsevier.com/international-journal-of-forecasting
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Economics and Finance | 71 | 54 | 82 | 22 |
The aim of the journal is to expand the discussion of research in Econometrics, Statistics, Series (mathematics), Consensus forecast and Autoregressive model. The majority of Econometrics studies are focused on the issues of Volatility (finance).
Econometrics, Statistics, Series (mathematics), Consensus forecast and Exponential smoothing are the main subjects of interest in the journal articles. Autoregressive model is a major topic of Econometrics research in the journal articles. The most cited papers address concerns in Probabilistic forecasting which are intertwined with other disciplines, such as Demand forecasting and Technology forecasting.
The journal explores disciplines such as Econometrics, Series (mathematics), Autoregressive model, Artificial intelligence and Machine learning. The Econometrics works featured in the journal incorporate elements from Expected shortfall and Nonlinear system. It explores issues in Series (mathematics) which can be linked to other research areas like Principal component analysis, Estimator, Mathematical optimization and Applied mathematics.
International Journal of Forecasting facilitates discussions on Autoregressive model that incorporate concepts from other fields like Vector autoregression and Nowcasting. The in-depth study on Artificial intelligence also explores topics in the intersecting field of Time series. Range (statistics) and Set (abstract data type) are some topics wherein Machine learning research discussed in the journal have an impact.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in International Journal of Forecasting (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in International Journal of Forecasting (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 6.87% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 18.12% were posted by at least one author from the top 10 institutions publishing in the journal. Another 10.07% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 9.40% of all publications and 62.42% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Another significant factor in the contribution to research at the International Journal of Forecasting are the educational institutions that the authors are affiliated with. The variety, reach and depth of research greatly depend on these affiliations. Education plays a foundational role in shaping research topics and methodologies, and therefore, it becomes pivotal to understand the role of educational institutions in this realm. For students aspiring to contribute towards Econometrics, Statistics, or similar fields, choosing the right educational institution that supports research activities becomes integral. If you're particularly interested in the field of accounting and based in Colorado, you might want to check the best accounting programs in Colorado. The affiliations of the authors in the International Journal of Forecasting not only represent their current professional entanglement, but it also serves as a testament to the quality of education and training they received. In turn, these institutions also benefit from the work of these researchers by solidifying their market presence in the field by producing high-quality and highly cited works. Research-oriented educational institutions provide the necessary infrastructure and a conducive environment that foster high-level research. Hence, a deeper understanding of these affiliations would benefit prospective students, researchers and academics alike.
Lu Wang;Feng Ma;Jing Liu;Lin Yang
(2020)Unknown
(2022)Manabu Asai;Rangan Gupta;Michael McAleer
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