I am working with data at the firm-year level where I am running a regression with standard errors clustered by firm. Because my dependent variable is a ratio between zero and one, I also estimate a fractional regression model. I noticed that the number of clusters in the fractional regression is greater than the number of clusters in the OLS regression containing the same variables and the same number of observations. Can someone please explain why? See an example of the same result below. Any thoughts are appreciated.

Code:
version 16
cls
webuse nlswork, clear
gen prop_wks_work = wks_work / (wks_work + wks_ue)
label variable prop_wks_work "Proportion of weeks worked last year"
assert 0<=prop_wks_work & prop_wks_work<=1 if !missing(prop_wks_work) // The dependent variable takes values between zero and one.

regress prop_wks_work age grade, vce(cluster idcode)
    quietly duplicates report idcode if e(sample)==1 // Store number of unique values of "idcode" in the sample.
    assert `e(N_clust)'==`r(unique_value)' // Number of clusters is equal to the number of unique values.

fracreg logit prop_wks_work age grade, vce(cluster idcode)
    quietly duplicates report idcode if e(sample)==1
    display `e(N_clust)'
    display `r(unique_value)'