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From |
nagi kayo <[email protected]> |

To |
statalist質問用 <[email protected]> |

Subject |
st: BOOTSTRAP: the standard errors of marginal effects of MIXLOGIT |

Date |
Sun, 3 Jun 2012 17:01:32 +0900 |

Dear Professor Arne Risa Hole and all I estimated mixed logit model using the command -mixlogit- and calculated the marginal effects using the command -mixlpred-. (Once again, I greatly appreciate that professor Arne Risa Holl gave me advice on how to calculate the marginal effects using "mixlpred" last february) However, now I am having trouble obtaining the standard errors and p-value of marginal effects using the bootstrap. First, please let me explain the data. My data set is like below. (Actually, my data set inlude 10,000 id, but here I show you the data only on two id for simplicity. In addition, the data I used in the estimation include the data on many household characteristics such as age, wealth, education level.) id alt d d1 d2 d3 d1inc d2inc d3inc d4inc p 1 1 1 1 0 0 665 0 0 0 0.214 1 2 0 0 1 0 0 665 0 0 0.186 1 3 0 0 0 1 0 0 665 0 0.381 1 4 0 0 0 0 0 0 0 665 0.219 2 1 0 1 0 0 779 0 0 0 0.553 2 2 1 0 1 0 0 779 0 0 0.301 2 3 0 0 0 1 0 0 779 0 0.107 2 4 0 0 0 0 0 0 0 779 0.039 id: households alt: 1=households are worried about their retirement life because the pension benefit is NOT enough. 2=households are worried about their retirement life for some reasons other than pension. 3=households are NOT worried about their retirement life because the pension benefit is enough. 4=households are NOT worried about their retirement life for some reasons other than pension. d: dummy which equals one if households choose "alt" in the same row. (so id 1 chose alt 1, and id 2 chose alt 2.) d1-d3: intercepts d1inc-d4inc: real households income p: an alternative specific variable using the above data, i did the estimation as follows: ********************************************************************** mixlogit d d1 d2 d3 d1inc d2inc d3inc, group(id) rand(p) mixlpred prep_base preserve quietly replace d1inc=d1inc+1 if alt==1 quietly replace d2inc=d2inc+1 if alt==2 quietly replace d3inc=d3inc+1 if alt==3 quietly replace d4inc=d4inc+1 if alt==4 mixlpred prep_inc cap program drop marginal_inc program marginal_inc, rclass quietly sum prep_base if alt==1 local av_prep_base1 = r(mean) quietly sum prep_inc if alt==1 local av_prep_inc1 = r(mean) return scalar marge_inc1 = `av_prep_inc1' - `av_prep_base1' quietly sum prep_base if alt==2 local av_prep_base2 = r(mean) quietly sum prep_inc if alt==2 local av_prep_inc2 = r(mean) return scalar marge_inc2 = `av_prep_inc2' - `av_prep_base2' quietly sum prep_base if alt==3 local av_prep_base3 = r(mean) quietly sum prep_inc if alt==3 local av_prep_inc3 = r(mean) return scalar marge_inc3 = `av_prep_inc3' - `av_prep_base3' quietly sum prep_base if alt==4 local av_prep_base4 = r(mean) quietly sum prep_inc if alt==4 local av_prep_inc4 = r(mean) return scalar marge_inc4 = `av_prep_inc4' - `av_prep_base4' end bootstrap r(marge_inc1), reps(1000): marginal_inc bootstrap r(marge_inc2), reps(1000): marginal_inc bootstrap r(marge_inc3), reps(1000): marginal_inc bootstrap r(marge_inc4), reps(1000): marginal_inc restore ************************************************************************ The results of bootstrap is as follows: Standard errors P-value marge_inc1 -0.0011 4.44e-06 0.000 marge_inc2 -0.0008 2.70e-06 0.000 marge_inc3 0.0013 5.41e-06 0.000 marge_inc4 0.0007 3.36e-06 0.000 ************************************************************************ Apparently, there is no problem in the above results. However, all the standard errors of marginal effects of ANY explanatory variable (e.g. age, education level, risk aversion) are very small, and all p-values of marginal effects of ANY explanatory variables are 0.000. I am wondering if my program has something wrong. Could anyone give me any comments? I greatly appreciate it. with best wishes, KAYO * * 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**:**st: Re: st: BOOTSTRAP: the standard errors of marginal effects of MIXLOGIT***From:*Arne Risa Hole <[email protected]>

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