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From |
"Maarten Buis" <[email protected]> |

To |
<[email protected]> |

Subject |
st: RE: Disentangle unobserved state effect |

Date |
Thu, 2 Aug 2007 12:02:25 +0200 |

--- Gao Liu wrote > I am examining the impacts of some state-imposed policies, measured as a set > of dummy variables, on school districts. Some states adopt some of these > policies, others not. But if a state adopts one policy, it would apply to > all school districts in the state. In other words, a policy dummy variable > has the same value for all school districts within the same state. > > The dataset is an unbalanced panel, containing a sample of school districts > from different states in different periods. School district that appear in > this period generally would not be in the dataset next period, although some > exceptions exist. Policies were adopted before the start period I am > looking at. And during my examining period, no states change their policies. > > The problem is: since the dummy variables of interest are linear combination > of states, we can't include state dummy variables. Thus, the results of the > impact of these policies on school districts may capture some unobserved > state-wide effects. It is not so convincing to simply interpret the > coefficients of those dummy variables as the policy impacts. Is there any > way to solve this problem? Your schools are nested in states, and you want to add a variable that remains constant at the state level. In that case you can't use a fixed effects model (add state dummies), but you can use a random effects model. Downside is that now you have to make assumptions about the unobserved state-wide effects (well, you could not expect it to be otherwise: the information about unobserved effects has to come from somewhere, if it is not from your observations (which it is not, otherwise it wouldn't be unobserved) and it is not from your design (as would be the case in a fixed effect model) than it has to come from your assumptions). In this case the assumption that troubles the most people is that the unobserved state wide effects are uncorrelated with the observed variables. But given your design, you don't have much choice. The Stata commands implementing these models are part of the -xt- family of commands, which one you choose depends on your dependent variable. See: -help xt- for a list of commands. Hope this helps, Maarten ----------------------------------------- Maarten L. Buis Department of Social Research Methodology Vrije Universiteit Amsterdam Boelelaan 1081 1081 HV Amsterdam The Netherlands visiting address: Buitenveldertselaan 3 (Metropolitan), room Z434 +31 20 5986715 http://home.fsw.vu.nl/m.buis/ ----------------------------------------- * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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