From: SYMON Paul [email@example.com]
Sent: Thursday, March 20, 2014 7:26 AM
To: Andrew Rose
Cc: Schaffer, Mark E; firstname.lastname@example.org; MITCHELL Stephanie; SCHRÖDER Sarah
Subject: Surprising Similarities: Recent Monetary Regimes of Small Economies
Attachments: Stata Rose.zip; ATT00001.htm; Edinburgh University charitable status
Dear Professor Rose,
We, i.e. Alex Kiermeier, Stephanie Mitchell, Sarah Schröder and Paul Symon are MSc. Economics students at the University of Edinburgh in the Scottish Graduate Program of Economics (SGPE). As part of our programme, we are currently working on an “Econometrics Project” (overseen by Prof. Mark Schaffer from Heriot-Watt University) and set out to replicate and challenge the findings of your recent working paper “Surprising Similarities: Recent Monetary Regimes of Small Economies.”
First and foremost we would like to thank you for allowing us access to your dataset and log files, especially for keeping everything so comprehensive. Having had a closer look at your dataset and your regressions, we highlighted some points you may or may not have come discovered since we accessed your files and wanted to share our results with you.
We found some duplicates in your dataset that change your results fairly insignificantly but thought you would still want to know. Attached in the zip file are copies of our log and do files that compare your original regressions in ptest1.log to the results when one drops the duplicates. We actually identified the issue when we tried to xtset your data. The observation that repeatedly crops up in the regressions is Sudan (2011) although this is not the only duplicate in your dataset, however we are not sure if the others are in someway intentional due to the different classifications of monetary regime. The other log file include does exactly the same thing for the xtivreg regressions.
We also have reason to believe that the model may be estimated in a fashion other than the conventional Random Effects GLS. You may have noticed that in several of your regressions the sigma_u=0. This suggests that Random Effects degenerates to a Pooled OLS, which can be verified by using the ‘regress’ in place of ‘xtreg’. Ordinarily one would proceed by performing a Hausman Test, however as you mention fixed effects is not applicable due to the lack of between orthogonality conditions. We test the consistency of Random Effects by using Mundlak fixed effects where the dependent variable is regressed on the explanatory variables and the mean of the explanatory variables. By using ‘xtoverid’ command (package xtoverid from http://fmwww.bc.edu/RePEc/bocode/x) we test whether the additional orthogonality conditions of the Random Effects estimator are overidentifying, thus rendering Random Effects inconsistent. The log file is also attached for this procedure.
Our suggestion is that the time-variant regressors are driving the rejection of the null and that this can be avoided by estimating them using only the within orthogonality conditions and the time invariant regressors using only the between orthogonality conditions. This is what we are working towards and would be more than happy to share our finished project with you if you are interested?
Your paper was thoroughly enjoyable to work with and we hope that you find our insight useful. We would sincerely appreciate any feedback you may possibly offer.
Alex Kiermeier, Stephanie Mitchell, Sarah Schröder and Paul Symon
PS- One last small point, in Table 8 where you present the p-values for the Hypothesis test there is a typo with regards to the number of significance stars. There is a p-value in the third column second row (Income=0) that is equal to 0.14 that has been marked as highly significant (**). We double-checked and the p-value is correct it is just the stars that are not.