Comments (8)
What type of specification are you trying to run?
Is this a panel with individual fixed effects?
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What type of specification are you trying to run? Is this a panel with individual fixed effects?
Yes, a panel with individual fixed effects
from ivcrc.
Can you describe the specification you want to run?
(Meaning what are the variables, what's endogenous, what's time-varying, what's the instrument, etc.)
from ivcrc.
Unfortunately, "fe" is not an undocumented ivcrc option, so running
ivcrc y (x = z), fe
does not do anything with fixed effects. The module ignores "fe" and proceeds on the part it does understand: "ivcrc y (x =z)." The module does not automatically create dummy variables for fixed effects categories (factor variables more generally) or conduct within transformations the way commands like these
areg y x, absorb(id)
or
xtreg y x, fe
would work. However, stata's "xi: ..." wrapper is very flexible and can create temporary dummy variables from categorical data or IDs for most commands, including ivcrc. Other than using "xi: ...", you could manually generate dummies for each fixed effects category, or possibly use stata's within-transformation command "xtdata, fe" if demeaning makes econometric sense given the application.
from ivcrc.
The econometric issue here is the first stage quantile regression, which you cannot apply the within transformation to, and which will be subject to the incidental parameters problem.
However, it's possible you could justify the assumptions on an outcome model that has already been within-transformed.
Depends a bit on the specifics.
from ivcrc.
Meaning what are the variables, what's endogenous, what's time-varying, what's the instrument, etc
It's actually an unbalanced panel (5 periods, on average, 5000 individuals/periods)
the specification is as following:
Y_{ict}: the dependent variable ( i-individual, c-county, t-time)
X_{c,t}: the independent variable
Z_{c,t}: the instrument
H_{ict}: the time-varying control variables (including individual\county levels)
from ivcrc.
Unfortunately, "fe" is not an undocumented ivcrc option, so running
ivcrc y (x = z), fe
does not do anything with fixed effects. The module ignores "fe" and proceeds on the part it does understand: "ivcrc y (x =z)." The module does not automatically create dummy variables for fixed effects categories (factor variables more generally) or conduct within transformations the way commands like these
areg y x, absorb(id)
or
xtreg y x, fe
would work. However, stata's "xi: ..." wrapper is very flexible and can create temporary dummy variables from categorical data or IDs for most commands, including ivcrc. Other than using "xi: ...", you could manually generate dummies for each fixed effects category, or possibly use stata's within-transformation command "xtdata, fe" if demeaning makes econometric sense given the application.
Thanks!
from ivcrc.
The econometric issue here is the first stage quantile regression, which you cannot apply the within transformation to, and which will be subject to the incidental parameters problem. However, it's possible you could justify the assumptions on an outcome model that has already been within-transformed. Depends a bit on the specifics.
Thanks!
from ivcrc.
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