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From |
Kit Baum <baum@bc.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
RE: st: loglikelihood and loglikelihood ratio |

Date |
Wed, 18 Mar 2009 07:08:12 -0400 |

<>

Kit Baum | Boston College Economics and DIW Berlin | http://ideas.repec.org/e/pba1.html An Introduction to Stata Programming | http://www.stata-press.com/books/isp.html An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.html On Mar 18, 2009, at 02:33 , Jingjjing wrote:

My total dataset contains 7 regions. The estimation results for the 7 regions are fine. All R square are positive, all LR chi() are positive, and all degree of freedom are right. 2. I choose the last 4 regions of the total 7regions and create a new data set(changed the dummy variables). Here, all the R square are positive, all LR chi() are positive. But the degree of freedom are strange. 4 regions Unrestricted-----------------------------------------------------------------------Equation Obs Parms RMSE "R-sq" chi2 P-----------------------------------------------------------------------lnc 72 40 .0987079 0.9693 7.62e+07 0.0000 sl 72 8 .0230819 0.3033 417.70 0.0000 se 72 8 .0023162 0.9399 1246.72 0.0000 sm 72 8 .0292372 0.5744 1094.54 0.0000-----------------------------------------------------------------------_cons in equation lnc are dropped, no other variable droped 4 regions Restricted-----------------------------------------------------------------------Equation Obs Parms RMSE "R-sq" chi2 P-----------------------------------------------------------------------lnc 72 37 .0930231 0.9727 1.47e+07 0.0000 sl 72 7 .0195899 0.4982 347.11 0.0000 se 72 7 .0022661 0.9425 1275.65 0.0000 sm 72 7 .0270912 0.6346 1003.91 0.0000-----------------------------------------------------------------------No _cons dropped, no variable droppedLikelihood-ratio test LR chi2(2)= 6.71(Assumption: B nested in A) Prob > chi2= 0.0350I am thinking if the degree of freedom changed from 3 to 2 because of _cons in unrestricted model is dropped, but kept in restricted model? 3. I chose the first 3 regions and created them as a new dataset (changed the dummy variables). When I estimated equations lnc, sl, sm, se, there are two negative R square values. So I changed them to ln, sl, sk, se and got one negative R-sq this time. LR chi() here are negative.

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