CMP: Stata module to implement conditional (recursive) mixed process estimator
Abstractcmp estimates multi-equation, mixed process models, potentially with hierarchical random effects. "Mixed process" means that different equations can have different kinds of dependent variables. The choices are: continuous (like OLS), tobit (left-, right-, or bi-censored), probit, and ordered probit. "Conditional" means that the model can vary by observation. An equation can be dropped for observations for which it is not relevant--if, say, a worker retraining program is not offered in a city then the determinants of uptake cannot be modeled there. Or the type of dependent variable can vary by observation. A dependent variable in one equation can appear on the right side of another equation. Such dependencies must have a recursive structure if the dependencies are on censored variables as observed, meaning that they split the equations into stages. If the dependencies are on (latent) linear dependent variables, they can be recursive or simultaneous in structure. So cmp can fit many SUR, simultaneous equation, and IV models. cmp's modeling framework therefore embraces those of the official Stata commands probit, ivprobit, treatreg, biprobit, tetrachoric, oprobit, mprobit, asmprobit, asroprobit, tobit, ivtobit, cnreg, intreg, truncreg, heckman, heckprob, xtreg, xtprobit, xttobit, xtintreg, in principle even regress, sureg, and reg3. It goes beyond them in offering far more flexibility in model construction. The routine runs under Stata 10 or later, faster under Stata 11.2 or later.
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Bibliographic InfoSoftware component provided by Boston College Department of Economics in its series Statistical Software Components with number S456882.
Programming language: Stata
Requires: Stata version 10.1 and package ghk2 (q.v.); version 11 to use factor variables
Date of creation: 16 Oct 2007
Date of revision: 17 Sep 2014
Note: This module should be installed from within Stata by typing "ssc install cmp". Windows users should not attempt to download these files with a web browser.
Contact details of provider:
Postal: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA
Web page: http://fmwww.bc.edu/EC/
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For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F Baum).
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