Example of Journal of Applied Econometrics format
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Example of Journal of Applied Econometrics format Example of Journal of Applied Econometrics format Example of Journal of Applied Econometrics format Example of Journal of Applied Econometrics format Example of Journal of Applied Econometrics format Example of Journal of Applied Econometrics format Example of Journal of Applied Econometrics format Example of Journal of Applied Econometrics format Example of Journal of Applied Econometrics format Example of Journal of Applied Econometrics format Example of Journal of Applied Econometrics format Example of Journal of Applied Econometrics format
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open access Open Access ISSN: 8837252 e-ISSN: 10991255

Journal of Applied Econometrics — Template for authors

Publisher: Wiley
Categories Rank Trend in last 3 yrs
Social Sciences (miscellaneous) #35 of 334 down down by 19 ranks
Economics and Econometrics #119 of 661 down down by 53 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 261 Published Papers | 1055 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 26/06/2020
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Top papers
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FAQ

Journal Performance & Insights

  • Impact Factor
  • CiteRatio
  • SJR
  • SNIP

Impact factor 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.

1.901

7% from 2018

Impact factor for Journal of Applied Econometrics from 2016 - 2019
Year Value
2019 1.901
2018 2.053
2017 2.336
2016 2.117
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has decreased by 7% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

CiteRatio is a measure of average citations received per peer-reviewed paper published in the journal.

4.0

3% from 2019

CiteRatio for Journal of Applied Econometrics from 2016 - 2020
Year Value
2020 4.0
2019 3.9
2018 4.2
2017 4.4
2016 4.5
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 3% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR) measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

2.878

21% from 2019

SJR for Journal of Applied Econometrics from 2016 - 2020
Year Value
2020 2.878
2019 2.379
2018 2.817
2017 3.899
2016 2.654
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 21% in last years.
  • This journal’s SJR is in the top 10 percentile category.

Source Normalized Impact per Paper (SNIP) measures actual citations received relative to citations expected for the journal's category.

2.295

2% from 2019

SNIP for Journal of Applied Econometrics from 2016 - 2020
Year Value
2020 2.295
2019 2.244
2018 2.105
2017 2.388
2016 2.402
graph view Graph view
table view Table view

insights Insights

  • SNIP of this journal has increased by 2% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

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CiteRatio: 4.2 | SJR: 1.98 | SNIP: 2.249

Journal of Applied Econometrics

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Wiley

Journal of Applied Econometrics

The Journal of Applied Econometrics is an international journal published bi-monthly, plus 1 additional issue (total 7 issues). It aims to publish articles of high quality dealing with the application of existing as well as new econometric techniques to a wide variety of probl...... Read More

Social Sciences

i
Last updated on
26 Jun 2020
i
ISSN
0883-7252
i
Impact Factor
High - 2.095
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
Yellow faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
apa
i
Citation Type
Author Year
(Blonder et al., 1982)
i
Bibliography Example
Blonder, G. E., Tinkham, M., & Klapwijk, T. M. (1982). Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys. Rev. B, 25(7), 4515–4532.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1002/JAE.616
Bounds testing approaches to the analysis of level relationships
M. Hashem Pesaran1, Yongcheol Shin2, Richard Smith3

Abstract:

This paper develops a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend- or first-difference stationary. The proposed tests are based on standard F- and t-statistics ... This paper develops a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend- or first-difference stationary. The proposed tests are based on standard F- and t-statistics used to test the significance of the lagged levels of the variables in a univariate equilibrium correction mechanism. The asymptotic distributions of these statistics are non-standard under the null hypothesis that there exists no level relationship, irrespective of whether the regressors are I(0) or I(1). Two sets of asymptotic critical values are provided: one when all regressors are purely I(1) and the other if they are all purely I(0). These two sets of critical values provide a band covering all possible classifications of the regressors into purely I(0), purely I(1) or mutually cointegrated. Accordingly, various bounds testing procedures are proposed. It is shown that the proposed tests are consistent, and their asymptotic distribution under the null and suitably defined local alternatives are derived. The empirical relevance of the bounds procedures is demonstrated by a re-examination of the earnings equation included in the UK Treasury macroeconometric model. Copyright © 2001 John Wiley & Sons, Ltd. read more read less

Topics:

Asymptotic distribution (54%)54% related to the paper, Null hypothesis (51%)51% related to the paper, Variables (50%)50% related to the paper, Univariate (50%)50% related to the paper
View PDF
11,141 Citations
open accessOpen access Journal Article DOI: 10.1002/JAE.951
A simple panel unit root test in the presence of cross-section dependence
M. Hashem Pesaran1

Abstract:

A number of panel unit root tests that allow for cross section dependence have been proposed in the literature that use orthogonalization type procedures to asymptotically eliminate the cross dependence of the series before standard panel unit root tests are applied to the transformed series. In this paper we propose a simple... A number of panel unit root tests that allow for cross section dependence have been proposed in the literature that use orthogonalization type procedures to asymptotically eliminate the cross dependence of the series before standard panel unit root tests are applied to the transformed series. In this paper we propose a simple alternative where the standard ADF regressions are augmented with the cross section averages of lagged levels and first-differences of the individual series. New asymptotic results are obtained both for the individual CADF statistics, and their simple averages. It is shown that the individual CADF statistics are asymptotically similar and do not depend on the factor loadings. The limit distribution of the average CADF statistic is shown to exist and its critical values are tabulated. Small sample properties of the proposed test are investigated by Monte Carlo experiments. The proposed test is applied to a panel of 17 OECD real exchange rate series as well as to log real earnings of households in the PSID data. read more read less

Topics:

Unit root test (57%)57% related to the paper, Unit root (56%)56% related to the paper
View PDF
3,972 Citations
open accessOpen access Journal Article DOI: 10.1002/1099-1255(200009/10)15:5<447::AID-JAE570>3.0.CO;2-1
Mixed mnl models for discrete response
Daniel McFadden1, Kenneth Train1

Abstract:

SUMMARY Thispaperconsidersmixed,orrandomcoeAcients,multinomiallogit (MMNL)modelsfordiscreteresponse, andestablishesthefollowingresults.Undermildregularityconditions,anydiscretechoicemodelderivedfrom random utility maximization has choice probabilities that can be approximated as closely as one pleases by a MMNLmodel.Practical... SUMMARY Thispaperconsidersmixed,orrandomcoeAcients,multinomiallogit (MMNL)modelsfordiscreteresponse, andestablishesthefollowingresults.Undermildregularityconditions,anydiscretechoicemodelderivedfrom random utility maximization has choice probabilities that can be approximated as closely as one pleases by a MMNLmodel.PracticalestimationofaparametricmixingfamilycanbecarriedoutbyMaximumSimulated LikelihoodEstimationorMethodofSimulatedMoments,andeasilycomputedinstrumentsareprovidedthat make the latter procedure fairly eAcient. The adequacy of a mixing specification can be tested simply as an omittedvariabletestwithappropriatelydefinedartificialvariables.Anapplicationtoaproblemofdemandfor alternativevehiclesshowsthatMMNL provides aflexible and computationally practical approach todiscrete response analysis. Copyright # 2000 John Wiley & Sons, Ltd. read more read less

Topics:

Mixed logit (56%)56% related to the paper, Mixing (physics) (54%)54% related to the paper
View PDF
3,557 Citations
open accessOpen access Journal Article DOI: 10.1002/JAE.659
Computation and analysis of multiple structural change models
Jushan Bai1, Pierre Perron2

Abstract:

In a recent paper, Bai and Perron (1998) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the proble... In a recent paper, Bai and Perron (1998) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the problem of estimation of the break dates and present an efficient algorithm to obtain global minimizers of the sum of squared residuals. This algorithm is based on the principle of dynamic programming and requires at most least-squares operations of order O(T2) for any number of breaks. Our method can be applied to both pure and partial structural change models. Second, we consider the problem of forming confidence intervals for the break dates under various hypotheses about the structure of the data and the errors across segments. Third, we address the issue of testing for structural changes under very general conditions on the data and the errors. Fourth, we address the issue of estimating the number of breaks. Finally, a few empirical applications are presented to illustrate the usefulness of the procedures. All methods discussed are implemented in a GAUSS program. Copyright © 2002 John Wiley & Sons, Ltd. read more read less

Topics:

Structural break (54%)54% related to the paper, Residual sum of squares (53%)53% related to the paper, Model selection (52%)52% related to the paper, Linear model (51%)51% related to the paper, Asymptotic distribution (51%)51% related to the paper
View PDF
3,509 Citations
open accessOpen access Journal Article DOI: 10.1002/(SICI)1099-1255(199611)11:6<601::AID-JAE417>3.0.CO;2-T
Numerical distribution functions for unit root and cointegration tests
James G. MacKinnon1

Abstract:

SUMMARY This paper employs response surface regressions based on simulation experiments to calculate distribution functions for some well-known unit root and cointegration test statistics. The principal contributions of the paper are a set of data files that contain estimated response surface coefficients and a computer progr... SUMMARY This paper employs response surface regressions based on simulation experiments to calculate distribution functions for some well-known unit root and cointegration test statistics. The principal contributions of the paper are a set of data files that contain estimated response surface coefficients and a computer program for utilizing them. This program, which is freely available via the Internet, can easily be used to calculate both asymptotic and finite-sample critical values and P-values for any of the tests. Graphs of some of the tabulated distribution functions are provided. An empirical example deals with interest rates and inflation rates in Canada. Tests of the null hypothesis that a time-series process has a unit root have been widely used in recent years, as have tests of the null hypothesis that two or more integrated series are not cointegrated. The most commonly used unit root tests are based on the work of Dickey and Fuller (1979) and Said and Dickey (1984). These are known as Dickey-Fuller (DF) tests and Augmented Dickey-Fuller (ADF) tests, respectively. These tests have non-standard distributions, even asymptotically. The cointegration tests developed by Engle and Granger (1987) are closely related to DF and ADF tests, but they have different, non-standard distributions, which depend on the number of possibly cointegrated variables. Although the asymptotic theory of these unit root and cointegration tests is well developed, it is not at all easy for applied workers to calculate the marginal significance level, or P-value, associated with a given test statistic. Until a few years ago (MacKinnon, 1991), accurate critical values for cointegration tests were not available at all. In a recent paper (MacKinnon, 1994), I used simulation methods to estimate the asymptotic distributions of a large number of unit root and cointegration tests. I then obtained reasonably simple approximating equations that may be used to obtain approximate asymptotic P-values. In the present paper, I extend the results to allow for up to 12 variables, instead of six, and I correct two deficiencies of the earlier work. The first deficiency is that the approximating equations are considerably less accurate than the underlying estimated asymptotic distributions. The second deficiency is that, even though the simulation experiments provided information about the finite-sample distributions of the test statistics, the approximating equations were obtained only for the asymptotic case. The key to overcoming these two deficiencies is to use tables of response surface coefficients, from which estimated quantiles for any sample size may be calculated, instead of equations to read more read less

Topics:

Unit root (58%)58% related to the paper, Asymptotic theory (statistics) (58%)58% related to the paper, Test statistic (55%)55% related to the paper, Cointegration (55%)55% related to the paper, Statistical hypothesis testing (51%)51% related to the paper
2,802 Citations
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Journal of Applied Econometrics format uses apa citation style.

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Absolutely not! With our tool, you can freely write without having to focus on LaTeX. You can write your entire paper as per the Journal of Applied Econometrics guidelines and autoformat it.

Yes. The template is fully compliant as per the guidelines of this journal. Our experts at SciSpace ensure that. Also, if there's any update in the journal format guidelines, we take care of it and include that in our algorithm.

Sure. We support all the top citation styles like APA style, MLA style, Vancouver style, Harvard style, Chicago style, etc. For example, in case of this journal, when you write your paper and hit autoformat, it will automatically update your article as per the Journal of Applied Econometrics citation style.

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One little Google search can get you the Word template for any journal. However, why do you need a Word template when you can write your entire manuscript on SciSpace, autoformat it as per Journal of Applied Econometrics's guidelines and download the same in Word, PDF and LaTeX formats? Try us out!.

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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 those factors the review board, rejection rates, frequency of inclusion in indexes, Eigenfactor, etc. You must assess all the factors and then take the final call.

SHERPA/RoMEO Database

We have extracted this data from Sherpa Romeo to help our researchers understand the access level of this journal. The following table indicates the level of access a journal has as per Sherpa Romeo 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.

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S. No. Citation Style Type
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2. Numbered
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4. Author Year (Cited Pages)
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SciSpace would allow download of your references in Journal of Applied Econometrics Endnote style, according to wiley guidelines.

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