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From |
kokootchke <kokootchke@hotmail.com> |

To |
statalist <statalist@hsphsun2.harvard.edu> |

Subject |
st: Model selection using AIC/BIC and other information criteria |

Date |
Tue, 23 Jun 2009 19:07:02 -0400 |

Dear all, I have a model that says that the return or yield spread of a bond issued by a country depends non-linearly on the country's probability of default. If I assume that this probability of default follows a logistic form, I get that the log spread depends linearly on "stuff" which I take to be macroeconomic variables. To choose the best model, I use AIC/BIC. One interesting fact I observe is that in some cases, I see that both AIC and BIC select a model that contains some variable X even when a lot of data points are missing for that particular variable, which means I actually lose a lot of observations when I include such variable X. More specifically, I have: MODEL 1 regress log_spread a b c X estat ic which gives AIC = 915 then, MODEL 2 regress log_spread a b c estat ic which gives AIC = 1500 but the OLS in model 1 uses 1200 observations while the OLS in model 2 uses 2800 observations (because 1600 observations are missing in variable X)!! You would think that this would be because X is very relevant to explain the spread, but in fact I see some cases when this variable is statistically insignificant!! Can any of you explain this? Alternatively, could you tell me whether there are any other useful stats I could look at? Thank you very much! Best, Adrian _________________________________________________________________ Bing™ brings you maps, menus, and reviews organized in one place. Try it now. http://www.bing.com/search?q=restaurants&form=MLOGEN&publ=WLHMTAG&crea=TEXT_MLOGEN_Core_tagline_local_1x1 * * 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: Model selection using AIC/BIC and other information criteria***From:*Richard Williams <Richard.A.Williams.5@ND.edu>

**References**:**st: Analyze a subpopulation of survey data in Stata 10.1***From:*"Karadogan, Figen" <fo145502@ohio.edu>

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