# st: ivreg2, cluster vs. state fixed effects

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## st: ivreg2, cluster vs. state fixed effects

 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 * *   For searches and help try: *   http://www.stata.com/help.cgi?search*   http://www.stata.com/support/statalist/faq*   http://www.ats.ucla.edu/stat/stata/