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From |
Maarten buis <[email protected]> |

To |
[email protected] |

Subject |
Re: st: predicting fitted values after ivtobit |

Date |
Mon, 4 Feb 2008 16:53:30 +0000 (GMT) |

--- Alejandro Delafuente <[email protected]> wrote: > Am trying to show graphically the relationship between a score index > (X - independent variable) and remittance levels (Y - dependent > variable) estimated with an ivtobit model. > > Thus far, after running the ivtobit model I predict marginal effects > as follows: > mfx compute, at(mean X = numerical value) > > As part of the above computation Stata displays the (predicted) > fitted values for Y. I repeat the above command across a full range > of different levels of the score index, leaving the rest of > independent variables fixed at their mean, to obtain predicted values > of remittances and then manually plot the estimated values against > the different levels of the score index. > > That said, I have two questions: > Is this the right way to predict expected levels of remittances, > considering that am doing some left censoring at zero? In other > words, am I using the corrected 'fitted values' command? With Tobit like commands there are multiple types of predicted values possible, all of them are correct. What can be incorrect is your interpretation. Given that you are dealing with remittance I assume that your variable is censored at zero, and you are interested in the actual value of the remittance (which is either 0 or positive) and not in the latent remittance (which can be negative, 0, or positive) nor in the probability of remittance. Your command gives you the latent remittance. > Is there any graphic option that would allow Stata do this for me > more directly (i.e, to use an overlayed picture of the scatter of > actual observations and then the fitted values above it), although my > score index has many values I would use -predict- after replacing the variables you want to keep constant by their mean. See the example below: *---------------- begin example ------------------------ sysuse auto, clear // weight and length are measured in too small units, // making the regression coefficients too small to be // easily interpretable, moreover as I am a real // European I am used to the metric system ;-) // transform weight in metric tonnes replace weight = weight/2204.62262 label variable weight "Weight (tonnes)" // transform lenth in meters replace length = length/39.3700787 label variable length "Length (meters)" // transform miles per gallon in kilometers per litre replace mpg = mpg/2.35214584 label variable mpg "kilometers per litre" // For illustration purposes the mpg is asumed to // censored at 7.5 km/litre replace mpg = 7.5 if mpg <= 7.5 tobit mpg weight length foreign, ll(7.5) sum length if e(sample) gen length_temp = length replace length = r(mean) gen foreign_temp = foreign replace foreign = 0 predict ystar_dom, ystar(7.5,.) replace foreign = 1 predict ystar_for, ystar(7.5,.) replace foreign = foreign_temp replace length = length_temp drop foreign_tem length_temp twoway scatter mpg weight if foreign == 0 || /// scatter mpg weight if foreign == 1, /// msymbol(x) || /// line ystar* weight, sort /// lpattern(shortdash longdash) /// ytitle("km per litre") /// note("predicted values are computed" /// "using mean values for length") /// legend(order(1 "domestic" /// 2 "foreign" /// - " " "predicted values" /// 3 "domestic" /// 4 "foreign" )) *--------------- end example -------------------------- (For more on how to use examples I sent to the Statalist, see http://home.fsw.vu.nl/m.buis/stata/exampleFAQ.html ) Hope this helps, Maarten ----------------------------------------- Maarten L. Buis Department of Social Research Methodology Vrije Universiteit Amsterdam Boelelaan 1081 1081 HV Amsterdam The Netherlands visiting address: Buitenveldertselaan 3 (Metropolitan), room Z434 +31 20 5986715 http://home.fsw.vu.nl/m.buis/ ----------------------------------------- __________________________________________________________ Sent from Yahoo! Mail - a smarter inbox http://uk.mail.yahoo.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/

**Follow-Ups**:**Re: st: predicting fitted values after ivtobit***From:*Alejandro Delafuente <[email protected]>

**References**:**st: predicting fitted values after ivtobit***From:*Alejandro Delafuente <[email protected]>

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