Replication in R

R code that regenerates the numbers this paper reports, starting from the dataset published on this site. It reproduces 22 of 23. The one that does not match is listed below.

Run it

Rscript run.R

run.R is the whole package. Save it and run it: it reads the dataset from this site if the CSV is not sitting beside it, and loads the shared conventions file the same way, so it works on its own in an empty directory. It needs R with fixest, and depending on the paper lme4, metafor, plm, BMS or LowRankQP. It writes results.json, one value per number, each named for where it appears in the paper.

How it compares with Stata

Most of these papers were estimated in Stata, and the two programs differ in places that change printed digits. Those conventions are stated once, in stata_compat.R, and shared by every replication on this site: ivreg2's large-sample variance, SSC winsor's order statistics, xtreg's treatment of singleton groups, and the restricted-ML default of xtmixed, which is not the default of the mixed command that replaced it.

Numbers that do not match the printed paper

Cells are named as they are in results.json. The reason for each difference follows the table.

cellpaperthis code
BMA best-practice global estimate (%), own reconstruction-0.014-0.019053

rebuilt from Table 5's BMA posterior means, which the paper prints to three decimals; the 14 rounded coefficients leave a near-constant offset of about +0.005 across all 21 countries. Re-running the authors' BMS chain is not possible with the wrappers in stata_compat.R, so this is an approximation, not a reproduction, and is not scored as either.

Files