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From |
KONSTANTARAS KONSTANTINOS <dinokon@otenet.gr> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: confused with nlogit |

Date |
Tue, 17 Feb 2009 18:03:49 +0200 (EET) |

Dear statalisters, I try to run a nested logit analysis in order to combine two (hypothetical) decision steps: 1) default or no default (2 outcomes)

I should mention that all independent variables are individual specific –no alternative specific covariates exist. I use the nlogit command hence expand my data –expand 4-, create the choice variable cho4 to indicate which bottom case has been selected, create a level 1 variable to indicate the top level choice –called deftype-. As explanatory variables I use variables that have been found statistically significant for explaining the level-1 case in a binomial logit setting (named X covariates) and different covariates found significant for the 3 additional outcomes -once in default- (named Z). I run a clogit initially to see the results and I get reasonable estimates for the parameters of the 3 “defaulted” cases in comparison to the non-default outcome. I use as covariates for the problem the explanatory variables multiplied by the indicator variables for each choice, i.e. a2*X a3*X a4*X for explanatory variable X and for the 3 choices –the a1 corresponds to the base case. The problem starts when I introduce the nlogit level 1 equation: a)if I try to use as explanatory covariates the a2*Z a3*Z a4*Z the program stops, as it cannot find any variation for the level 1 situation. Same if I use a dummy nonsense covariate (noth1): nlogit cho4 (al=aa2X aa3X aa4X) (deftype= aa2Z aa3Z aa4Z) , group(patt) notree aa2Z is not a characteristic of deftype, model is unidentified. nlogit cho4 (al=aa2X aa3X aa4X) (deftype=noth1) , group(patt) notree note: aa2X omitted due to no within-group variance note: aa3X omitted due to no within-group variance note: aa4X omitted due to no within-group variance no independent variables for al model b) utilizing new covariates crated by multiplying level one choice (deftype) times the explanatory variable Z the program converges with difficulty –huge coefficients- to a solution that is not statistically significant –huge S.E. Iteration 15: Coefficient vector:

deftype: deftype: default: nodef: deftypeZ deftypeZ _cons _cons y1 -.0895932 -21841.72 18693.3 -35.58853 .015625h log likelihood = -248.95039 (not concave) I am certainly doing something wrong here, but I would appreciate it if you could offer me some guidance. I have read previous questions but cannot decipher my wrongdoing. (I am using Stata 9.2 SE). Thanking you in advance,

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