[Nick Barton]

Thanks for the helpful tips Ben! Obtaining the correct ATT with weights is no problem but I am struggling a bit on where to put the weights into the G so the IF is calculated correctly. I saw on p.60 of the aforementioned paper you explain the use of survey weights for the logistic regression example. This clarifies that instead of N one should use the sum of weights (W), and in the simple case the weight w just goes into the cross product. For the various G_subscripts, I am not sure exactly how this applies. G11 is the simplest case, but for the others I am unsure. I tried out several things but didn't get the right ATT using csdid_rif, so would be grateful of further guidance.

preserve
 keep if year==2022 & female==0
mata  Dnm = "treat"; Xnm = "$controls"
Ynm = "outcome" ; Znm = "$controls"
N = st_nobs()
D = st_data(., Dnm); X = st_data(., Xnm), J(N, 1, 1)
Y = st_data(., Ynm); Z = st_data(., Znm), J(N, 1, 1)
w = st_data(., "weight")
W = sum(W)  

// estimate logit and create weights
stata("quietly logit " + Dnm + " " + Xnm + " [pw=weight]")
p = invlogit(X * st_matrix("e(b)")')
w0 = p :/ (1 :- p) :* !D
st_store(., st_addvar("double", "w0"), w0)
stata("gen est_weight=w0*weight")
w0_weight = "est_weight"
est_weight = st_data(., w0_weight)  

// estimate regression model
stata("quietly regress " + Ynm + " " + Znm + " if " + Dnm + "==0 [iw=est_weight]")  
Zg0 = Z * st_matrix("e(b)")'  
// compute IF for eta01  
h1 = X :* (D - p)  
G11inv = invsym(cross(X, w :* p :* (1 :- p), X) / W) //I think this is now ok after adding w and W  
h2 = Z :* w0 :* (Y :- Zg0) //Should this use est_weight instead of w0?  
G21 = cross(-h2, X) / W //Needs editing  
G22inv = invsym(cross(Z, w0, Z) / W) //Needs editing, perhaps using est_weight instead of w0 or equivalently w:* w0?  
eta01 = mean(Zg0, D:* w)  

h3 = D :* (Zg0 :- eta01)  G32 = colsum(-D :* Z) / W //Needs editing  
IF_eta01 = W/sum(D:* w) * (h3 - (h2 - h1 * G11inv' * G21') * G22inv' * G32')  //Not sure here

// compute IF for eta11  
eta11 = mean(Y, D:* w)  
IF_eta11 = W/sum(D:* w) * D:* w :* (Y :- eta11) //Needs editing  

// compute IF for ATT  
ATT = eta11 - eta01  
ATT  
st_local("att", strofreal(ATT)) //added to store the att in a local to calculate the RIF from the IF    

IF_ATT = IF_eta11 - IF_eta01  
st_store(., st_addvar("double", "if_att"), IF_ATT) //added to store the IF for all observations  
// display results (point estimate, mean of IF, standard error)  
(ATT, eta11, eta01)', mean((IF_ATT, IF_eta11, IF_eta01))', sqrt(diagonal(variance((IF_ATT, IF_eta11, IF_eta01)) / W)) * sqrt((W-1)/W)  
end  

sum if_att //check whether the IF is on average 0  
*Calculate the RIF from IF produced above
cap drop RIF_att
gen RIF_att=if_att+`att'  

*Now obtain the ATT with clustered standard errors
csdid_rif RIF_att, cluster(cluster_var)  

*Save for male population
keep id RIF_att year
rename RIF_att RIF_male
tempfile male_merge
save `male_merge'  
restore

Then repeat for female==1 and merge that onto the main dataset too and use csdid_rif followed by the test command.

[Nick Barton]

Upon further review, I edited the G_subscripts to the following:

G11inv = invsym(cross(X, w :* p :* (1 :- p), X) / W)
G21 =  cross( -h2, X :* w ) / W
G22inv = invsym(cross( Z, w :* w0, Z) / W)
G32 = colsum( -D:* Z :* w) / W

I also dropped a "w" from here, since it didn't make sense to weight the dummy for an observation being treated or not in this outcome:

 IF_eta11 = W/sum(D:* w) * D:* (Y :- eta11)

While it is much closer to the teffects ipwra estimate, it is still not quite there

[Nick Barton]

Sorry for spamming the thread, but I now realised that if I run

sum RIF_att if_att [iw=weight1]

Then I actually get exactly what I would expect, i.e. the RIF mean is the ATT and the IF mean is close to zero.

Furthermore, to get a RIF value that can be used by csdid_rif, it is necessary to reweight the RIF

sum weight1 if !mi(RIF_att)
gen RIF_att_weighted=RIF_att*weight/`r(mean)'

csdid_rif RIF_att_weighted, cluster(clustervar)

This then gives the correct ATT from the csdid command, allowing for merging back together and testing.

[Felipe Lozano]

Dear Fernando, and others.

I was wondering if there was an example to compare the ATTs from two different RIFs from csdid. I see that the code from drdid produces some variables that can be compared using the csdid_rif postestimation command, but from the information within the RIFs from csdid, I have a hard time to make the analogy.

I started with the following code:

use RIF1, clear
csdid_stats simple, wboot estore(simple1)
use RIF2, clear
csdid_stats simple, wboot estore(simple2)
test simple1= simple2

And I obtain the error simple 1 not found.


Sorry if this was pointed out at a different spot, but I have been reading this thread out of the title.

Thanks

Felipe LR

[FernandoRios]

Hi felipe
i do not have an example in hand. However I can suggest where to start
so you already have two rif files. You need to merge them together based on the panel Id. Then use csdid_rif to create the table of interest
hth