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From |
L S <[email protected]> |

To |
[email protected] |

Subject |
st: Inequality Restrictions with CLogit |

Date |
Sat, 2 May 2009 12:24:06 -0700 |

Hello, I am trying to estimate a simple logit binary discrete choice model using clogit. For example, utility for person i from option j is given by U(ij) = b1*x1(ij) + b2*x2(ij) + e(ij) where the error e is distributed Type 1 Extreme Value. Currently, in my data, I am receiving a nonsensical negative sign on b1—I would like to restrict the maximum likelihood estimation to have b1 be positive. I came across the following post on maximum likelihood (ML) estimation with interval constraints, which seems fairly related: http://www.stata.com/support/faqs/stat/intconst.html It seems that, while inequality restrictions are not directly built into STATA, one can implement them by replacing b1 with exp(c): U(ij) = exp(c)*x1(ij) + b2*x2(ij) + e(ij) and then estimating c and b2, as the expression exp(c) will always be positive. My question is: How would one actually program this in practice using clogit? Can one actually use clogit with this, or is it necessary to use ML? To get some data to see the issue at hand, one can do: webuse lowbirth clogit low lwt smoke, group(pairid) How could one restrict the coefficient on lwt to be positive? (I have no idea for this data if this restriction would make sense.) Thanks a lot! * * 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/

**Follow-Ups**:**Re: st: Inequality Restrictions with CLogit***From:*Maarten buis <[email protected]>

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