An Overview of Economics and Econometrics Related R Packages

This study provides a systematic overview of 207 econometrics-related R packages identified through CRAN and the Econometrics Task View. Using descriptive and inferential statistics and text mining to compute the word frequency and association among words (n-grams and correlations), we evaluate the development patterns, documentation practices, publication outcomes, and methodological scope. The findings reveal that most packages are created by small-to-mid-sized teams in Europe and North America, with mid-sized collaborations and packages including vignettes being significantly more likely to achieve journal publication. While reverse dependencies indicate strong ecosystem integration, they do not predict publication, and Bayesian or dataset-only packages remain underrepresented. Growth has accelerated since 2010, but newer packages exhibit fewer updates, raising concerns about sustainability. These findings highlight both the central role of R in contemporary econometrics and the need for broader participation, methodological diversity, and long-term maintenance.

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Stats
Published
2025-09-26
DOI
https://doi.org/10.3390/stats8040085
Primary Topic
Data Analysis with R
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article
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article

An Overview of Economics and Econometrics Related R Packages

Michail Tsagris, Christos Adam, Despina Michelaki
Stats
Data Analysis with R
article

An Overview of Economics and Econometrics Related R Packages

Michail Tsagris, Christos Adam, Despina Michelaki
article en

Abstract

This study provides a systematic overview of 207 econometrics-related R packages identified through CRAN and the Econometrics Task View. Using descriptive and inferential statistics and text mining to compute the word frequency and association among words (n-grams and correlations), we evaluate the development patterns, documentation practices, publication outcomes, and methodological scope. The findings reveal that most packages are created by small-to-mid-sized teams in Europe and North America, with mid-sized collaborations and packages including vignettes being significantly more likely to achieve journal publication. While reverse dependencies indicate strong ecosystem integration, they do not predict publication, and Bayesian or dataset-only packages remain underrepresented. Growth has accelerated since 2010, but newer packages exhibit fewer updates, raising concerns about sustainability. These findings highlight both the central role of R in contemporary econometrics and the need for broader participation, methodological diversity, and long-term maintenance.

StatsVol. 8(4)
University of Crete (GR), Crete University Press (GR)
Openalex Percentile: Top 86%
Data Analysis with R
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An Overview of Economics and Econometrics Related R Packages — Michail Tsagris, Christos Adam, et al. · Stats (2025) | TGRS Research Map | TGRS