Example of International Journal of Computational Economics and Econometrics format
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Example of International Journal of Computational Economics and Econometrics format Example of International Journal of Computational Economics and Econometrics format Example of International Journal of Computational Economics and Econometrics format Example of International Journal of Computational Economics and Econometrics format Example of International Journal of Computational Economics and Econometrics format Example of International Journal of Computational Economics and Econometrics format Example of International Journal of Computational Economics and Econometrics format
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Example of International Journal of Computational Economics and Econometrics format Example of International Journal of Computational Economics and Econometrics format Example of International Journal of Computational Economics and Econometrics format Example of International Journal of Computational Economics and Econometrics format Example of International Journal of Computational Economics and Econometrics format Example of International Journal of Computational Economics and Econometrics format Example of International Journal of Computational Economics and Econometrics format
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This content is only for preview purposes. The original open access content can be found here.
open access Open Access

International Journal of Computational Economics and Econometrics — Template for authors

Categories Rank Trend in last 3 yrs
Economics and Econometrics #494 of 661 up up by 82 ranks
Computer Science Applications #575 of 693 down down by 13 ranks
journal-quality-icon Journal quality:
Medium
calendar-icon Last 4 years overview: 79 Published Papers | 67 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 06/07/2020
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Related Journals

open access Open Access
recommended Recommended

Springer

Quality:  
High
CiteRatio: 7.4
SJR: 0.847
SNIP: 1.986
open access Open Access

IEEE

Quality:  
High
CiteRatio: 6.4
SJR: 0.786
SNIP: 2.027
open access Open Access
recommended Recommended

Taylor and Francis

Quality:  
High
CiteRatio: 5.9
SJR: 0.972
SNIP: 1.349
open access Open Access
recommended Recommended

Taylor and Francis

Quality:  
High
CiteRatio: 6.6
SJR: 0.813
SNIP: 1.434

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

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

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.

0.8

33% from 2019

CiteRatio for International Journal of Computational Economics and Econometrics from 2016 - 2020
Year Value
2020 0.8
2019 0.6
2018 0.4
graph view Graph view
table view Table view

0.223

45% from 2019

SJR for International Journal of Computational Economics and Econometrics from 2018 - 2020
Year Value
2020 0.223
2019 0.154
2018 0.158
graph view Graph view
table view Table view

0.337

74% from 2019

SNIP for International Journal of Computational Economics and Econometrics from 2018 - 2020
Year Value
2020 0.337
2019 0.194
2018 0.127
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 33% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has increased by 45% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 74% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

International Journal of Computational Economics and Econometrics

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Inderscience Publishers

International Journal of Computational Economics and Econometrics

Approved by publishing and review experts on SciSpace, this template is built as per for International Journal of Computational Economics and Econometrics formatting guidelines as mentioned in Inderscience Publishers author instructions. The current version was created on 06 Jul 2020 and has been used by 332 authors to write and format their manuscripts to this journal.

i
Last updated on
06 Jul 2020
i
ISSN
1757-1170
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Yellow faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
plainnat
i
Citation Type
Author Year
(Blonder et al., 1982)
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Bibliography Example
Beenakker, C. W. J. (2006). ‘Specular Andreev Reflection in Graphene’. Phys. Rev. Lett., Vol 97, No 6, pp. 067007.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1504/IJCEE.2018.10007883
medsem: a Stata package for statistical mediation analysis
Mehmet Mehmetoglu1

Abstract:

The Stata package medsem provides a post-estimation command testing mediational hypotheses using Baron and Kenny's (1986) approach modified by Iacobucci et al. (2007) as well as an alternative approach proposed by Zhao et al. (2010) after estimating the concerned mediational model with the built-in sem command of Stata. The p... The Stata package medsem provides a post-estimation command testing mediational hypotheses using Baron and Kenny's (1986) approach modified by Iacobucci et al. (2007) as well as an alternative approach proposed by Zhao et al. (2010) after estimating the concerned mediational model with the built-in sem command of Stata. The primary benefit of medsem is that it can contribute to conducting a proper and complete mediational analysis based on even very complex models (including observed and/or latent variables and with multiple mediators) due to the simultaneous estimation capability of structural equation modelling (SEM) technique. read more read less

Topics:

Mediation (statistics) (51%)51% related to the paper, Structural equation modeling (51%)51% related to the paper
View PDF
77 Citations
Journal Article DOI: 10.1504/IJCEE.2015.066207
Determinants of non–performing loans in Ghana banking industry

Abstract:

The detrimental effect non–performing loans (NPLs) have on banks' income and the economy makes it necessary to examine the determinants of NPLs in the banking industry in Ghana. Using panel regression model, it was found that both bank–specific variables (i.e., previous year's NPL, bank size, net interest margin (NIM), and cu... The detrimental effect non–performing loans (NPLs) have on banks' income and the economy makes it necessary to examine the determinants of NPLs in the banking industry in Ghana. Using panel regression model, it was found that both bank–specific variables (i.e., previous year's NPL, bank size, net interest margin (NIM), and current year's loan growth) and macroeconomic variables (i.e., previous year's inflation, real gross domestic product (GDP) per capita growth and real effective exchange rate) significantly affect NPLs in the banking industry. Also the sub–sample estimations showed that both bank–specific (i.e., previous year's NPLs and current year's loan growth) and macroeconomic factors (i.e., real effective exchange rate, real GDP per capita growth, and previous year's inflation rate) affect NPLs of large banks. However, whereas bank–specific variables (i.e., previous year's NPLs and current year's loan growth) are important in explaining NPLs, macroeconomic factors are not important in explaining NPLs for small banks. read more read less

Topics:

Real gross domestic product (54%)54% related to the paper, Non-performing loan (53%)53% related to the paper, Net interest margin (51%)51% related to the paper
54 Citations
Journal Article DOI: 10.1504/IJCEE.2014.060294
Are commodity price shocks important? A Bayesian estimation of a DSGE model for Russia

Abstract:

This paper constructs a DSGE model for an economy with commodity exports. We estimate the model using Russian data, making a special focus on quantitative effects of commodity price dynamics. There is a widespread belief that economic activity in Russia crucially depends on oil prices, but quantitative estimates are scarce. W... This paper constructs a DSGE model for an economy with commodity exports. We estimate the model using Russian data, making a special focus on quantitative effects of commodity price dynamics. There is a widespread belief that economic activity in Russia crucially depends on oil prices, but quantitative estimates are scarce. We estimate an oil price effect on the Russian economy in a general equilibrium framework. Our setup is similar to those of Kollmann (2001) and Dam and Linaa (2005), but we extend their models by explicitly accounting for oil revenues. In addition to standard supply, demand, cost–push, and monetary policy shocks, we include the shock of commodity export revenues. The main objective of the paper is to identify the contribution of structural shocks to business cycle fluctuations in the Russian economy. We found that despite a strong impact on GDP from commodity export shocks, business cycles in Russia are mostly domestically based. read more read less

Topics:

Supply shock (63%)63% related to the paper, Commodity (Marxism) (57%)57% related to the paper, Dynamic stochastic general equilibrium (56%)56% related to the paper, General equilibrium theory (52%)52% related to the paper, Demand shock (52%)52% related to the paper
View PDF
49 Citations
open accessOpen access Journal Article DOI: 10.1504/IJCEE.2009.029151
Bank efficiency and share prices in China: empirical evidence from a three-stage banking model

Abstract:

This paper examines the relationship between the efficiency of China banks and its share price performance. Our analysis consists of three parts. First, we calculate the annual share price returns of the banks for each year between 1997 and 2006. Then we employ the data envelopment analysis (DEA) window analysis method to est... This paper examines the relationship between the efficiency of China banks and its share price performance. Our analysis consists of three parts. First, we calculate the annual share price returns of the banks for each year between 1997 and 2006. Then we employ the data envelopment analysis (DEA) window analysis method to estimate the efficiency of each bank. Finally, we regress the annual share price returns on the change in efficiency, while controlling for other bank specific traits. The empirical findings suggest that large Chinese banks have exhibited higher technical and pure technical efficiency levels compared to their small and medium sized bank counterparts, while the medium sized banks have exhibited higher scale efficiency. The relationship between Chinese banks' efficiency and share price performance suggest that bank efficiency estimates derived from the DEA window analysis method contributes significant information towards share price returns beyond that provided by financial information. read more read less

Topics:

Share price (62%)62% related to the paper, Chinese financial system (59%)59% related to the paper, Data envelopment analysis (56%)56% related to the paper
View PDF
31 Citations
Journal Article DOI: 10.1504/IJCEE.2014.060284
Forecasting the real price of oil using online search data
Dean Fantazzini, Nikita Fomichev1

Abstract:

New models to forecast the real price of oil on the basis of macroeconomic indicators and Google search data are proposed. A large–scale out–of–sample forecasting analysis comparing the different models is performed. It is found that models including both Google data and macroeconomic aggregates statistically outperform the c... New models to forecast the real price of oil on the basis of macroeconomic indicators and Google search data are proposed. A large–scale out–of–sample forecasting analysis comparing the different models is performed. It is found that models including both Google data and macroeconomic aggregates statistically outperform the competing models in the short term, while multivariate models including only Google data perform best also for medium and long term forecasts up to 24 months ahead. This finding is confirmed by different robustness checks. read more read less

Topics:

Robustness (economics) (59%)59% related to the paper, Term (time) (51%)51% related to the paper, Online search (50%)50% related to the paper
28 Citations
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International Journal of Computational Economics and Econometrics format uses plainnat citation style.

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1. Can I write International Journal of Computational Economics and Econometrics in LaTeX?

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

2. Do you follow the International Journal of Computational Economics and Econometrics guidelines?

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3. Can I cite my article in multiple styles in International Journal of Computational Economics and Econometrics?

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 International Journal of Computational Economics and Econometrics citation style.

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5. Can I use a manuscript in International Journal of Computational Economics and Econometrics 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 International Journal of Computational Economics and Econometrics that you can download at the end.

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

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13. What is Sherpa RoMEO Archiving Policy for International Journal of Computational Economics and Econometrics?

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 International Journal of Computational Economics and Econometrics. 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 International Journal of Computational Economics and Econometrics?

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

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

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16. Can I download International Journal of Computational Economics and Econometrics 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 International Journal of Computational Economics and Econometrics Endnote style according to Elsevier guidelines.

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