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st: RE: How to avoid negative fitted values


From   "Craig, Benjamin M." <Benjamin.Craig@moffitt.org>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: How to avoid negative fitted values
Date   Fri, 20 Aug 2010 23:18:09 -0400

There are two ways that make sense to me, but their use depends on your theory.
 
1. glm with a log link will produce positive estimates (see work of manning and mullahy)
 
2. Inequality constraints on the parameter space (much more difficult)
 
It sound like you are using a linear model on skewed data, and you are overshooting the skew by assuming a symmetric distribution. Maybe if you assume a gamma distribution (see Basu) your predictions will get better. Again this is all dependent on your theory about the origin of the error. I am not in real estate, sorry.
 
Ben
 
 
Benjamin M. Craig, Ph.D. Assistant Member, Health Outcomes & Behavior Moffitt Cancer Center Associate Professor, Department of Economics University of South Florida Contact Information 12902 Magnolia Drive, MRC-CANCONT Tampa, FL 33612-9416 Phone: (813) 745-6710 Fax: (813) 745-6525 benjamin.craig@moffitt.org

________________________________

From: owner-statalist@hsphsun2.harvard.edu on behalf of Laurie Molina
Sent: Fri 8/20/2010 10:26 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: How to avoid negative fitted values



Dear statalist,

I am triying to imput rental prices for houses to a sample using some
characteristics of the construction which are shared between my data
and the data in another database in which rental prices are declared.

When i use OLS i get negative fitted values both in the original
database as in my database.

How can ensure that the predicted values will be non negative?

Thank you very much in advance.

Laurie
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