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From |
Duha Altindag <daltin2@tigers.lsu.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: ivreg2, cluster vs. state fixed effects |

Date |
Thu, 11 Feb 2010 13:00:24 -0600 |

You can use egen [new_var_name]=group(state year) to create groups for state-years. On Thu, Feb 11, 2010 at 6:28 AM, Nirina F <fstata@gmail.com> wrote: > > 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/ * * 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/

**References**:**st: ivreg2, cluster vs. state fixed effects***From:*Nirina F <fstata@gmail.com>

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