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From |
Renuka Metcalfe <rm18203@yahoo.co.uk> |

To |
statalist@hsphsun2.harvard.edu |

Date |
Wed, 14 Nov 2007 16:13:48 +0000 (GMT) |

Dear Statalisters I am new to using IV regression. I estimated a random effects GLS equation -xtreg Y x1 x2 x3 x4 x5-10, re I believe x1=own training is endogenous x2, x3 and x4 are endogenous. The rest I believe are not. I am using cross-section data and x1 is binary. Do I have this variable as x1a if they have had training and x1b (where I set x1b=0 if they have had no training) if they have not had training. Is it best to deal with one endogenous variable at a time. (2) I am not certain as to the best way to deal with it either. Does one estimate a probit thus: -probit x1 x2 (without putting the instrument for training) x3 x4 then -predict x2hat -xtivreg Y (x2=instrument for training, bwd) x2hat x3 x4 ..., re The instrument for training, bwd was created as follows: bwd=. bwd=1 if they have had training bwd=0 if they have not had training (3) Is it better to estimate xtivreg in my case, rather than -ivreg-. (4) Should I then look if bwd is significant. Does the sign matter. A priori would one expect the sign to be negative if this variable is not endogenous to the dependent variable. (5) Would expect the own training variable to be negative and significant if training is not endogenous to Y. (6)Then does one do the -hausmen wu- test. If I want training to be non-endogenous to Y, what would be my a priori expectations. I would be grateful, if you would confirm the above. Thanks in advance Renuka ___________________________________________________________ Yahoo! Answers - Got a question? Someone out there knows the answer. Try it now. http://uk.answers.yahoo.com/ * * 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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