Dear all,
I am estimating a 2SLS for the following equation from a microdata at
individual level:
Y = b0+ b1*X1 +X2 ' *b2
where Y and X1 are dummy variables and X1 is endogenous and will be
instrumented with Z. X2 is a vector of control variables.
I only have one instrument and it is from a state level data because
it is the number of hospitals that the individual has in her state.
Therefore, I cannot use state-fixed effects anymore as otherwise, Z
will get dropped automatically due to collinearity.
Therefore, the model isn't identified with state effects, because
implicitly, I am using state as IV.
I am thinking of clustering the standard errors on state, so am I
right to just run the following?
ivreg2 y (x1=z) x2, cluster (state)
I tried to put under cluster state dummies but I realized that I can
only put one variable under cluster.
So I am wondering how do people cluster by region-year level? because
if we just gen a variable
gen regyr=region*year and then put that variable under cluster then we
might get trapped in the magic of multiplication.
suppose my region is coded from 1 to 4 and year from 1 to 5, then
2*3=3*2=6 therefore I cannot say those who are from region 2 and born
in 3 are in the same group as those who are from region 3 and born in
year 2.
Also, after clustering my coefficient on b1 became insignificant and
decreased in value.
This is the results I get from loneway of x1 against z (as may be you
have other suggestions for me on how to deal with this identification
problem?)
loneway x1 z
One-way Analysis of Variance for x1:
Number of obs = 33385
R-squared = 0.1178
Source SS df MS F Prob > F
-------------------------------------------------------------------------
Between z 903.19067 23 39.269159 193.61 0.0000
Within z 6766.5203 33361 .20282726
-------------------------------------------------------------------------
Total 7669.7109 33384 .22974212
Intraclass Asy.
correlation S.E. [95% Conf. Interval]
------------------------------------------------
0.12599 0.04266 0.04237 0.20961
Estimated SD of z effect .1709937
Estimated SD within z .4503635
Est. reliability of a z mean 0.99483
(evaluated at n=1336.11)
Thank you in advance for your time and for your help,
Nirina
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