Example of Computational Economics format
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Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format
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Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format Example of Computational Economics format
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open access Open Access

Computational Economics — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Economics, Econometrics and Finance (miscellaneous) #45 of 159 down down by 16 ranks
Computer Science Applications #363 of 693 down down by 43 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 385 Published Papers | 902 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 07/06/2020
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Related Journals

open access Open Access

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Taylor and Francis

Quality:  
High
CiteRatio: 6.4
SJR: 0.884
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Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

1.317

11% from 2018

Impact factor for Computational Economics from 2016 - 2019
Year Value
2019 1.317
2018 1.185
2017 1.038
2016 1.053
graph view Graph view
table view Table view

2.3

35% from 2019

CiteRatio for Computational Economics from 2016 - 2020
Year Value
2020 2.3
2019 1.7
2018 1.6
2017 1.8
2016 1.5
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 11% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 35% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

0.352

1% from 2019

SJR for Computational Economics from 2016 - 2020
Year Value
2020 0.352
2019 0.349
2018 0.365
2017 0.433
2016 0.47
graph view Graph view
table view Table view

0.891

8% from 2019

SNIP for Computational Economics from 2016 - 2020
Year Value
2020 0.891
2019 0.97
2018 0.921
2017 0.834
2016 0.699
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 1% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 8% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Computational Economics

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Springer

Computational Economics

Computational Economics has been accepted for Science Citation Index Expanded, Social Sciences Citation Index, and Current Contents/Social and Behavioral Sciences and will first appear with an Impact Factor in the 2010 Journal Citation Reports (JCR), published in June 2011. Co...... Read More

Economics, Econometrics and Finance

i
Last updated on
07 Jun 2020
i
ISSN
0927-7099
i
Impact Factor
Medium - 0.528
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
SPBASIC
i
Citation Type
Author Year
(Blonder et al, 1982)
i
Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

Journal Article DOI: 10.1023/A:1008655831209
Applied General Equilibrium Modeling with MPSGE as a GAMS Subsystem: AnOverview of the Modeling Framework and Syntax
Thomas F. Rutherford1
01 Oct 1999 - Computational Economics

Abstract:

This paper describes a programming environment for economic equilibrium analysis. The system introduces the Mathematical Programming System for General Equilibrium analysis (MPSGE, Rutherford 1987) within the Generalized Algebraic Modelling System (GAMS, Brooke, Kendrick and Meeraus (1988)). This arrangement exploits GAMS‘ se... This paper describes a programming environment for economic equilibrium analysis. The system introduces the Mathematical Programming System for General Equilibrium analysis (MPSGE, Rutherford 1987) within the Generalized Algebraic Modelling System (GAMS, Brooke, Kendrick and Meeraus (1988)). This arrangement exploits GAMS‘ set-oriented algebraic syntax for data manipulation and report writing. The system based on the tabular MPSGE input format provides a compact, non-algebraic representation of a model‘s nonlinear equations. This paper provides an overview of the modelling environment and three worked examples in tax policy analysis. read more read less

Topics:

Algebraic modeling language (63%)63% related to the paper, Syntax (programming languages) (50%)50% related to the paper
View PDF
642 Citations
open accessOpen access Posted Content
Productivity and Intermediate Products: A Frontier Approach
Rolf Färe1, Shawna Grosskopf1
01 Jan 1995 - Computational Economics

Abstract:

The purpose of this paper is to introduce a frontier model for productivity measurement that explicitly recognizes that some inputs are produced and consumed within the production technology. Here we differ from Koopmans (1951) by assuming that the intermediate inputs may also be final output. This assumption is in line with ... The purpose of this paper is to introduce a frontier model for productivity measurement that explicitly recognizes that some inputs are produced and consumed within the production technology. Here we differ from Koopmans (1951) by assuming that the intermediate inputs may also be final output. This assumption is in line with current international trade theory, where intermediate inputs are tradable. Our model consists of two production units that are interconnected in a network to form a production technology. The productivity measure employed here is the so-called Malmquist productivity index. This index consists of ratios of distance functions. Here these distance functions are defined on the network technology and they are computed using linear programming techniques. read more read less

Topics:

Productivity model (64%)64% related to the paper, Productivity (60%)60% related to the paper, Total factor productivity (57%)57% related to the paper, Production (economics) (56%)56% related to the paper
439 Citations
Journal Article DOI: 10.1007/S10614-017-9716-2
Extracting Appropriate Nodal Marginal Prices for All Types of Committed Reserve
01 Jan 2019 - Computational Economics

Abstract:

This paper proposes a framework to extract appropriate locational marginal prices for each type of reserve (up-/down-going reserves at both generation- and demand-sides). The proposed reserve pricing scheme accounts for the lost opportunity of selling the convertible products (energy and reserve). The fair prices can be obtai... This paper proposes a framework to extract appropriate locational marginal prices for each type of reserve (up-/down-going reserves at both generation- and demand-sides). The proposed reserve pricing scheme accounts for the lost opportunity of selling the convertible products (energy and reserve). The fair prices can be obtained for capacity reserves applying this framework, since this framework assigns the same prices to the same services provided at the same location. The proposed reserve pricing scheme provides all the market participants with the appropriate signals to modify their offers according to the system operator requirements. The pricing problem is decomposed to different hourly sub-problems considering the bounding constraints. To show the effectiveness of the proposed algorithm, it is applied to the IEEE reliability test system and the results are discussed. read more read less
270 Citations
Journal Article DOI: 10.1023/A:1014957310778
Heterogeneous Beliefs, Risk and Learning in a Simple Asset Pricing Model
Carl Chiarella1, Xue-Zhong He1
01 Feb 2002 - Computational Economics

Abstract:

Trade among individuals occurs either because tastes (risk aversion) differ, endowments differ, or beliefs differ. Utilising the concept of `adaptively rational equilibrium' and a recent framework of Brock and Hommes [6, 7] this paper incorporates risk and learning schemes into a simple discounted present value asset price mo... Trade among individuals occurs either because tastes (risk aversion) differ, endowments differ, or beliefs differ. Utilising the concept of `adaptively rational equilibrium' and a recent framework of Brock and Hommes [6, 7] this paper incorporates risk and learning schemes into a simple discounted present value asset price model with heterogeneous beliefs. Agents have different risk aversion coefficients and adapt their beliefs (about future returns) over time by choosing from different predictors or expectations functions, based upon their past performance as measured by realized profits. By using both bifurcation theory and numerical analysis, it is found that the dynamics of asset pricing is affected by the relative risk attitudes of different types of investors. It is also found that the external noise and learning schemes can significantly affect the dynamics. Compared with the findings of Brock and Hommes [7] on the dynamics caused by change of the intensity of choice to switch predictors, it is found that many of their insights are robust to the generalizations considered: however, the resulting dynamical behavior is considerably enriched and exhibits some significant differences. read more read less

Topics:

Capital asset pricing model (57%)57% related to the paper, Risk aversion (55%)55% related to the paper, Asset (economics) (52%)52% related to the paper
224 Citations
Journal Article DOI: 10.1023/A:1008699112516
Credit Risk Assessment Using Statistical and MachineLearning: Basic Methodology and Risk Modeling Applications
J. Galindo1, P. Tamayo
01 Apr 2000 - Computational Economics

Abstract:

Risk assessment of financial intermediaries is an area of renewed interest due to the financial crises of the 1980's and 90's. An accurate estimation of risk, and its use in corporate or global financial risk models, could be translated into a more efficient use of resources. One important ingredient to accomplish this goal i... Risk assessment of financial intermediaries is an area of renewed interest due to the financial crises of the 1980's and 90's. An accurate estimation of risk, and its use in corporate or global financial risk models, could be translated into a more efficient use of resources. One important ingredient to accomplish this goal is to find accurate predictors of individual risk in the credit portfolios of institutions. In this context we make a comparative analysis of different statistical and machine learning modeling methods of classification on a mortgage loan data set with the motivation to understand their limitations and potential. We introduced a specific modeling methodology based on the study of error curves. Using state-of-the-art modeling techniques we built more than 9,000 models as part of the study. The results show that CART decision-tree models provide the best estimation for default with an average 8.31% error rate for a training sample of 2,000 records. As a result of the error curve analysis for this model we conclude that if more data were available, approximately 22,000 records, a potential 7.32% error rate could be achieved. Neural Networks provided the second best results with an average error of 11.00%. The K-Nearest Neighbor algorithm had an average error rate of 14.95%. These results outperformed the standard Probit algorithm which attained an average error rate of 15.13%. Finally we discuss the possibilities to use this type of accurate predictive model as ingredients of institutional and global risk models. read more read less

Topics:

Dynamic risk measure (57%)57% related to the paper, Financial risk (56%)56% related to the paper, Word error rate (53%)53% related to the paper, Risk assessment (53%)53% related to the paper, Probit (50%)50% related to the paper
217 Citations
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With SciSpace, you do not need a word template for Computational Economics.

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You can download a submission ready research paper in pdf, LaTeX and docx formats.

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Time taken to format a paper and Compliance with guidelines

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Computational Economics format uses SPBASIC citation style.

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Frequently asked questions

1. Can I write Computational Economics in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Computational Economics guidelines and auto format it.

2. Do you follow the Computational Economics guidelines?

Yes, the template is compliant with the Computational Economics guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Computational Economics?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Computational Economics citation style.

4. Can I use the Computational Economics templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Computational Economics.

5. Can I use a manuscript in Computational Economics that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Computational Economics that you can download at the end.

6. How long does it usually take you to format my papers in Computational Economics?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Computational Economics.

7. Where can I find the template for the Computational Economics?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Computational Economics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Computational Economics's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Computational Economics an online tool or is there a desktop version?

SciSpace's Computational Economics is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Computational Economics?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Computational Economics?”

11. What is the output that I would get after using Computational Economics?

After writing your paper autoformatting in Computational Economics, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Computational Economics's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Computational Economics?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Computational Economics. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Computational Economics?

The 5 most common citation types in order of usage for Computational Economics are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Computational Economics?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Computational Economics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Computational Economics in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Computational Economics Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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