Example of Journal of Business and Economic Statistics format
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Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format Example of Journal of Business and Economic Statistics format
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Journal of Business and Economic Statistics — Template for authors

Publisher: Taylor and Francis
Categories Rank Trend in last 3 yrs
Social Sciences (miscellaneous) #10 of 334 up up by 47 ranks
Statistics and Probability #13 of 239 up up by 29 ranks
Statistics, Probability and Uncertainty #11 of 152 up up by 15 ranks
Economics and Econometrics #59 of 661 up up by 88 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 216 Published Papers | 1279 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 06/06/2020
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FAQ

Related Journals

open access Open Access

Springer

Quality:  
Good
CiteRatio: 1.2
SJR: 0.461
SNIP: 0.731
open access Open Access

Wiley

Quality:  
Good
CiteRatio: 2.2
SJR: 1.131
SNIP: 1.399
open access Open Access

Taylor and Francis

Quality:  
Good
CiteRatio: 2.7
SJR: 1.061
SNIP: 1.483
open access Open Access

Springer

Quality:  
Good
CiteRatio: 1.9
SJR: 0.507
SNIP: 1.109

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.

2.935

8% from 2018

Impact factor for Journal of Business and Economic Statistics from 2016 - 2019
Year Value
2019 2.935
2018 2.716
2017 2.115
2016 1.658
graph view Graph view
table view Table view

5.9

26% from 2019

CiteRatio for Journal of Business and Economic Statistics from 2016 - 2020
Year Value
2020 5.9
2019 4.7
2018 3.3
2017 2.8
2016 3.0
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 8% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 26% 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.

5.062

67% from 2019

SJR for Journal of Business and Economic Statistics from 2016 - 2020
Year Value
2020 5.062
2019 3.04
2018 2.886
2017 3.664
2016 2.59
graph view Graph view
table view Table view

4.015

49% from 2019

SNIP for Journal of Business and Economic Statistics from 2016 - 2020
Year Value
2020 4.015
2019 2.686
2018 1.827
2017 1.698
2016 1.648
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 67% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 49% in last years.
  • This journal’s SNIP is in the top 10 percentile category.
Journal of Business and Economic Statistics

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Taylor and Francis

Journal of Business and Economic Statistics

The Journal of Business and Economic Statistics ( JBES ) publishes a range of articles, primarily applied statistical analyses of microeconomic, macroeconomic, forecasting, business, and finance related topics. More general papers in statistics, econometrics, computation, simu...... Read More

Social Sciences

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Last updated on
05 Jun 2020
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ISSN
0735-0015
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Impact Factor
High - 2.499
i
Open Access
No
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Sherpa RoMEO Archiving Policy
Green faq
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Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
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Bibliography Name
Taylor and Francis Custom Citation
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Citation Type
Numbered
[25]
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Bibliography Example
Blonder GE, Tinkham M, Klapwijk TM. Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys Rev B. 1982; 25(7):4515–4532. Available from: 10.1103/PhysRevB.25.4515.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1198/073500102753410372
Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis
Eric Zivot1, Donald W.K. Andrews1

Abstract:

Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil-price shock. His analysis covers the Nelson–Plosser macroeconomic data series as well as a postwar quarterly real gross n... Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil-price shock. His analysis covers the Nelson–Plosser macroeconomic data series as well as a postwar quarterly real gross national product (GNP) series. His tests reject the unit-root null hypothesis for most of the series. This article takes issue with the assumption used by Perron that the Great Crash and the oil-price shock can be treated as exogenous events. A variation of Perron's test is considered in which the breakpoint is estimated rather than fixed. We argue that this test is more appropriate than Perron's because it circumvents the problem of data-mining. The asymptotic distribution of the estimated breakpoint test statistic is determined. The data series considered by Perron are reanalyzed using this test statistic. The empirical results make use of the asymptotics developed for the test stati... read more read less

Topics:

Test statistic (62%)62% related to the paper, Unit root test (59%)59% related to the paper, Dickey–Fuller test (57%)57% related to the paper, Unit root (55%)55% related to the paper, Alternative hypothesis (53%)53% related to the paper
View PDF
6,608 Citations
Journal Article DOI: 10.1198/073500102288618487
Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models
Robert F. Engle1

Abstract:

Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the flexibility of univari... Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be estimated very simply with univariate or two-step methods based on the likelihood function. It is shown that they perform well in a variety of situations and provide sensible empirical results. read more read less

Topics:

Conditional variance (68%)68% related to the paper, Autoregressive conditional heteroskedasticity (65%)65% related to the paper, Univariate (61%)61% related to the paper, Multivariate statistics (53%)53% related to the paper, Likelihood function (51%)51% related to the paper
View PDF
5,695 Citations
open accessOpen access Report DOI: 10.3386/T0169
Comparing Predictive Accuracy
Francis X. Diebold1, Roberto S. Mariano2

Abstract:

We propose and evaluate explicit tests of the null hypothesis of no difference in the accuracy of two competing forecasts. In contrast to previously developed tests, a wide variety of accuracy measures can be used (in particular, the loss function need not be quadratic and need not even be symmetric), and forecast errors can ... We propose and evaluate explicit tests of the null hypothesis of no difference in the accuracy of two competing forecasts. In contrast to previously developed tests, a wide variety of accuracy measures can be used (in particular, the loss function need not be quadratic and need not even be symmetric), and forecast errors can be non-Gaussian, nonzero mean, serially correlated, and contemporaneously correlated. Asymptotic and exact finite-sample tests are proposed, evaluated, and illustrated. read more read less

Topics:

Sign test (50%)50% related to the paper
View PDF
5,628 Citations
Journal Article DOI: 10.1198/073500102288618658
A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments
James H. Stock1, Jonathan H. Wright2, Motohiro Yogo3

Abstract:

Weak instruments arise when the instruments in linear instrumental variables (IV) regression are weakly correlated with the included endogenous variables. In generalized method of moments (GMM), more generally, weak instruments correspond to weak identification of some or all of the unknown parameters. Weak identification lea... Weak instruments arise when the instruments in linear instrumental variables (IV) regression are weakly correlated with the included endogenous variables. In generalized method of moments (GMM), more generally, weak instruments correspond to weak identification of some or all of the unknown parameters. Weak identification leads to GMM statistics with nonnormal distributions, even in large samples, so that conventional IV or GMM inferences are misleading. Fortunately, various procedures are now available for detecting and handling weak instruments in the linear IV model and, to a lesser degree, in nonlinear GMM. read more read less

Topics:

Generalized method of moments (52%)52% related to the paper, Instrumental variable (52%)52% related to the paper
View PDF
3,038 Citations
open accessOpen access Journal Article DOI: 10.1198/073500102317351921
Macroeconomic Forecasting Using Diffusion Indexes
James H. Stock1, Mark W. Watson1

Abstract:

This article studies forecasting a macroeconomic time series variable using a large number of predictors. The predictors are summarized using a small number of indexes constructed by principal component analysis. An approximate dynamic factor model serves as the statistical framework for the estimation of the indexes and cons... This article studies forecasting a macroeconomic time series variable using a large number of predictors. The predictors are summarized using a small number of indexes constructed by principal component analysis. An approximate dynamic factor model serves as the statistical framework for the estimation of the indexes and construction of the forecasts. The method is used to construct 6-, 12-, and 24-monthahead forecasts for eight monthly U.S. macroeconomic time series using 215 predictors in simulated real time from 1970 through 1998. During this sample period these new forecasts outperformed univariate autoregressions, small vector autoregressions, and leading indicator models. read more read less

Topics:

Dynamic factor (56%)56% related to the paper, Univariate (53%)53% related to the paper
View PDF
2,686 Citations
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Journal of Business and Economic Statistics format uses Taylor and Francis Custom Citation citation style.

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Frequently asked questions

1. Can I write Journal of Business and Economic Statistics in LaTeX?

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

2. Do you follow the Journal of Business and Economic Statistics guidelines?

Yes, the template is compliant with the Journal of Business and Economic Statistics 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 Journal of Business and Economic Statistics?

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 Journal of Business and Economic Statistics citation style.

4. Can I use the Journal of Business and Economic Statistics 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 Journal of Business and Economic Statistics.

5. Can I use a manuscript in Journal of Business and Economic Statistics 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 Journal of Business and Economic Statistics that you can download at the end.

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

7. Where can I find the template for the Journal of Business and Economic Statistics?

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8. Can I reformat my paper to fit the Journal of Business and Economic Statistics'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. Journal of Business and Economic Statistics an online tool or is there a desktop version?

SciSpace's Journal of Business and Economic Statistics 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 Journal of Business and Economic Statistics?

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 Journal of Business and Economic Statistics?”

11. What is the output that I would get after using Journal of Business and Economic Statistics?

After writing your paper autoformatting in Journal of Business and Economic Statistics, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Journal of Business and Economic Statistics'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 Journal of Business and Economic Statistics?

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 Journal of Business and Economic Statistics. 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 Journal of Business and Economic Statistics?

The 5 most common citation types in order of usage for Journal of Business and Economic Statistics 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 Journal of Business and Economic Statistics?

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 Journal of Business and Economic Statistics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Journal of Business and Economic Statistics 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 Journal of Business and Economic Statistics Endnote style according to Elsevier guidelines.

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