The Econometrics Journal‘s latest two-year Journal Impact Factor (JIF), 3.071, again places it among the best in its field (Journal Citation Reports 2021, Clarivate Analytics). At the same time, the journal’s longer run impact measures rose to record levels: Its 5-Year Journal Impact Factor (5YJIF) increased to 4.602, its Article Influence Score (AIS) to 4.370, and its Journal Citation Indicator (JCI) to 1.60.
The 2021 JIF equals the average number of times articles published in 2019 and 2020 were cited in 2021 (in Clarivate’s Web of Science). The JIF of The Econometrics Journal depends on a small number of citeable articles and may therefore be quite variable. Indeed, the JIF more than doubled last year, to again fall this year, to a level well above that of all earlier years. This can in part be traced back to one particularly high impact article,
- Chernozhukov, Chetverikov, Demirer, Duflo, Hansen, Newey, and Robins‘s “Double/debiased machine learning for treatment and structural parameters” (February 2018),
that contributed to the 2020 but not the 2021 JIF (the many readers with an interest in this paper may like its well documented implementation). It should be stressed though that three more high impact articles (and a long tail of other cited articles), contributed to the 2020 JIF, including two that also figure in the 2021 JIF:
- Botosaru and Ferman’s “On the role of covariates in the synthetic control method” (May 2019) and
- Baruník and Kley’s “Quantile coherency: A general measure for dependence between cyclical economic variables” (May 2019).
Moreover, the journal continued to publish impactful articles in 2020 and 2021, such as
- Calonico, Cattaneo, and Farrell’s “Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs” (May 2020),
- Cho’s “Quantifying the impact of non-pharmaceutical interventions during the COVID-19 outbreak: The case of Sweden” (September 2020),
- Knaus, Lechner, and Strittmatter’s “Machine learning estimation of heterogeneous causal effects: Empirical Monte Carlo evidence” (January 2021), and
- Semenova and Chernozhukov’s “Debiased machine learning of conditional average treatment effects and other causal functions” (May 2021).
Stanley Cho’s article was the first in a series of papers related to COVID-19 that the journal recently collected in a Virtual Issue on COVID-19. The last two papers continue the analysis and development of double/debiased machine learning of causal effects, just like some more recently accepted papers do.
The longer run impact measures consider impact over longer time periods. Therefore, they are more stable. Moreover, they permit articles more time to accrue citations, which may be important for an outlet like The Econometrics Journal, which has a quick review process and may therefore publish comparatively young papers. Specifically, as its name suggests, the 2021 5YJIF equals the average number of citations in 2021 to articles published over the previous five years (2016-2020). The 2021 AIS covers the same five years, but is adjusted for the quality of citations using data on the full network of citations. The JCI is a new three-year impact measure that seeks to control for differences between fields. All three measures rose to their highest levels ever this year.
The journal’s impact also continues to compare favorably to that of other specialized econometrics journals. Its 2021 JIF is just behind that of the Journal of Financial Econometrics and the Journal of Econometrics and well ahead of the Journal of Applied Econometrics and Econometric Theory. Its 5YJIF exceeds that of all but one of the specialized econometrics journals and its AIS and JCI are the highest in the field.
| Journal | JIF | 5YJIF | AIS | JCI |
|---|---|---|---|---|
| The Econometrics Journal | 3.071 | 4.602 | 4.370 | 1.60 |
| Journal of Financial Econometrics | 3.976 | 4.922 | 1.896 | 1.42 |
| Journal of Econometrics | 3.363 | 3.660 | 2.874 | 1.00 |
| Journal of Applied Econometrics | 2.460 | 3.487 | 2.656 | 0.95 |
| Econometric Theory | 1.968 | 2.286 | 2.088 | 0.71 |
| Econometric Reviews | 1.605 | 1.686 | 1.041 | 0.60 |
The journal’s 2021 impact is below that of a broad top journal in economics like Econometrica and a general statistics outlet like the Journal of the Royal Statistical Society Series B – Statistical Methodology (JRSSB). However, its AIS is aligned with those of, for example, the Journal of Business & Economic Statistics (JBES) and the Journal of the American Statistical Association (JASA). Moreover, its 2021 impact is well above that of Quantitative Economics.
| Journal | JIF | 5YJIF | AIS | JCI |
|---|---|---|---|---|
| Econometrica | 6.383 | 8.252 | 12.007 | 2.25 |
| JRSSB | 4.933 | 6.240 | 6.082 | 2.10 |
| Annals of Statistics | 4.904 | 5.640 | 5.071 | 1.88 |
| JBES | 5.309 | 5.396 | 4.612 | 1.75 |
| JASA | 4.369 | 5.773 | 4.365 | 1.84 |
| The Econometrics Journal | 3.071 | 4.602 | 4.370 | 1.60 |
| Quantitative Economics | 2.190 | 2.436 | 3.499 | 0.86 |
We are well aware that bibliometric analysis is imperfect and that impact measures and rankings may vary a lot from year to year, in particular for an outlet like The Econometrics Journal that publishes comparatively few papers. We are nonetheless pleased to see the overal upward trend in impact over the last few years, in particular because the journal started publishing more articles and publishing them faster at the same time. If anything, this suggests that the profession appreciates the journal’s focus on quick review and on econometrics that matters to applied work in economics.
