#thread follow up to previous thread below
i repeat the same excercise with positivity rate instead of reproduction rate vs stringency index by adding country, week and both effects in the panel regressions #COVID19 1/n
the graphs:
(notice higher positive rate when stringency stronger)
benchmark: within R² = 5.82%
+country dummies: same
+week dummies = 47.36% (~ x 100 w/r benchmark)
+country & week dum. = as above
again "seasonality" explains most of what is going on in the data #COVID19 2/n
and so again one can ask if they #lockdown during colder seasons and this makes actually things worse ? #COVID19
3/3
you can find me and similar stata monkey analysis on my TG channel: t.me/chrisgodlak
#thread
Following recent success of this thread (thanks @FatEmperor i guess :)just wanted to get back to this
i will just take the first graph as exemple: it's reproduction rate vs stringency index
panel (country-time in days) regression with random effects #COVID19 1/n
i put the initial graph as "benchmark" and i add 3 other graphs
panel regression with random effects
with countries dummies included
with weeks dummies included
with countries & weeks dummies included
and we will compare the R² as these are the only changing in this excercise 2/n
in panel regression what is most important is the R² within
adding country effects changes nothing
adding weeks (i.e. time trend or "seasonality" in this context) increases a lot the R² within (~ x100)
adding countries & weeks => same results as with weeks added only
3/n
Things that makes you go hmm
Reproduction rate vs Stringency index in Europe
overall R² = 2.36% #Covid_19
Hmm continues
Positive rate vs vs Stringency index in Europe
R²=3.99%
notice fitted values higher for positive rate when stringency index higher #Covid_19
another hmm
New cases per million vs Stringency index in Europe
R²=1.09% #Covid_19