Is it? Dropping 5 countries from the average is a human error, but this:
Herndon-Ash-Pollin find that they exclude Australia (1946-1950), New Zealand (1946-1949), and Canada (1946-1950). This has consequences, as these countries have high-debt and solid growth. Canada had debt-to-GDP over 90 percent during this period and 3 percent growth. New Zealand had a debt/GDP over 90 percent from 1946-1951. If you use the average growth rate across all those years it is 2.58 percent. If you only use the last year, as Reinhart-Rogoff does, it has a growth rate of -7.6 percent. That's a big difference, especially considering how they weigh the countries.
Unconventional Weighting. Reinhart-Rogoff divides country years into debt-to-GDP buckets. They then take the average real growth for each country within the buckets. So the growth rate of the 19 years that the U.K. is above 90 percent debt-to-GDP are averaged into one number. These country numbers are then averaged, equally by country, to calculate the average real GDP growth weight.
In case that didn't make sense, let's look at an example. The U.K. has 19 years (1946-1964) above 90 percent debt-to-GDP with an average 2.4 percent growth rate. New Zealand has one year in their sample above 90 percent debt-to-GDP with a growth rate of -7.6. These two numbers, 2.4 and -7.6 percent, are given equal weight in the final calculation, as they average the countries equally. Even though there are 19 times as many data points for the U.K.
It's hard to see how that doesn't make their findings nonsensical. Maybe it's because I am in research, but in science, it's not enough to fall in 'near agreement' with previous literature (and even here, the notion of 'agreement' is debatable) even if your methodology is bunk. Presenting a false analysis as a factual one makes it more difficult to make informed decisions, or to overturn previous interpretations in light of new or better evidence. Basically, if you are not going to do it right, don't do it at all. Otherwise, you screw everything up for everyone that is trying to understand how the world works.
These two presented cherry-picked and massaged the data that fit a narrative. It doesn't matter to which degree the narrative is true or not.