Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
| From | "Ed Levitas" <levitas@uwm.edu> |
| To | <statalist@hsphsun2.harvard.edu> |
| Subject | st: question about insturmental variables and probit/logits |
| Date | Mon, 3 Oct 2011 10:22:55 -0500 |
Hello Stata listers, A similar question to this has been asked before. Previous responses have suggested the use of QVF, GLLAMM, and similar programs. However, I don't think my data will allow me to follow these procedures. Simply, I have a dichotomous outcome, and an endogenous regressor. I also have two hierarchical levels (firms, and project development characteristics/year). For simplicity, assume one exogenous regressor and the endogenous regressor: DV = BExog(it) + BEndog(itk) where DV = 1 if firm i's kth project advances to a new stage of development by the end of year t, and zero otherwise Exog(it) = is a firm level exogenous regressor measured at the end of year t, and pertains to firm i. Endog(ikt) = is a project level endogenous regressor measured at the end of year t, pertaining to firm i's project k. Is the following an efficient way to estimate unbiased coefficients given my 2 levels of analysis? (note that I put arithmetic operators in for clarity but I do recognize that this is improper syntax for STATA) 1) XTREG Endog(itk) = BInst(itk) + BExog(it) (Where BInst is suitable instrument; ie highly correlated to Endog and highly uncorrelated to Exog ) 2) PREDICT yhat 3) BOOTSTRAP: XTLOGIT DV = BExog(it) + Byhat(itk), pa cluster(firm) Is this effective, or does it create additional biases? Thank you in advance for any suggestions/criticisms you have, Ed **************************************** Edward Levitas, PhD Associate Professor Sheldon B. Lubar School of Business University of Wisconsin-Milwaukee 3202 N. Maryland Ave. Milwaukee, WI 53211 ph: (414) 229-6825 fx: (414) 229-6957 http://www4.uwm.edu/business/faculty/busfaculty/levitas.cfm * * 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/