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From |
May Boggess <mboggess@stata.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Marginal & Impact Effects in a Tobit |

Date |
03 Aug 2004 12:34:42 -0500 |

On Tuesday, Gonzalo wrote: > I'm running a tobit with several dummies. > I calculated the marginal effect in the average probabilities and in the > average characteristics and the results are quite different from the ones > I obtain after the command 'dtobit' in Stata. Before I get started on -dtobit-, we must make certain we know what the formulas for the prediction functions following -tobit-. Here is some code that computes the predictions "by hand". Unfortunately, this is not simple, so I have used some local macroes, hoping that the expressions will be a little easier to understand that way: clear sysuse auto tobit mpg weight , ll(20) local xb=" _b[weight]*wei+_b[_cons] " local nn="norm((20-(_b[weight]*wei+_b[_cons]))/_b[_se])" local nd="normden((20-(_b[weight]*wei+_b[_cons]))/_b[_se])" local p 1 - `nn' local e `xb'+ _b[_se]*`nd'/(1 - `nn') local ys (`p')*(`e') + 20*`nn' predict xb,xb gen myxb=`xb' sum xb myxb predict p, p(20, .) di "`p'" gen myp=`p' sum p myp predict e, e(20, .) di "`e'" gen mye=`e' sum e mye predict ys, ys(20, .) di "`ys'" gen myys=`ys' sum ys myys Now, to compute discrete marginal effect we just take the difference between the value of the prediction at 1 and the value at 0. This is what -mfx- does, what and what the user-written command -dtobit- does. Unfortuntely, -dtobit- has a typo ( a 1 instead of an l) on line 239 of the ado code. Here is an example: clear sysuse auto tobit mpg for, ll(20) dtobit, brief local xb0=" _b[for]*0+_b[_cons] " local xb1=" _b[for]*1+_b[_cons] " local nn0="norm((20-(`xb0'))/_b[_se])" local nn1="norm((20-(`xb1'))/_b[_se])" local nd0="normden((20-(`xb0'))/_b[_se])" local nd1="normden((20-(`xb1'))/_b[_se])" local p0 1 - `nn0' local p1 1 - `nn1' local e0 `xb0'+ _b[_se]*`nd0'/(`p0') local e1 `xb1'+ _b[_se]*`nd1'/(`p1') local ys0 (`p0')*(`e0') + 20*`nn0' local ys1 (`p1')*(`e1') + 20*`nn1' mfx, predict(xb) display "mfx = " (`xb1')-(`xb0') mfx, predict(ystar(20, .)) display "mfx = " (`ys1')-(`ys0') mfx, predict(e(20, .)) display "mfx = " (`e1')-(`e0') mfx, predict(p(20, .)) display "mfx = " (`p1')-(`p0') You will notice the difference in ystar and e. To make the change to your copy of dtobit.ado, type which dtobit on the command line in Stata. That will tell you where the file is stored. Copy that, and use your favorite text editor to open the file. If your text editor shows you lines numbers, you won't have too much trouble finding line 239. It looks like this: scalar `E_c1' = `x1' + `se'*normd((`ll'-`x1')/`se') /* */ / (1-normprob((`l1'-`x1')/`se')) You want to change the l1 to an ll, so it will look like this: scalar `E_c1' = `x1' + `se'*normd((`ll'-`x1')/`se') /* */ / (1-normprob((`ll'-`x1')/`se')) Once you have made that change, you can rerun the above example, and you should find that now -dtobit- agrees with -mfx-. An update for -dtobit- will appear in the next Stata Journal. -- May mmb@stata.com * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Marginal & Impact Effects in a Tobit***From:*gonwei@adinet.com.uy

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