-------------------------------------------------------------------------------
help for mvppred                             Cappellari and Jenkins (31oct2002)
-------------------------------------------------------------------------------

Predictions from multivariate probit models estimated by SML

mvppred newvarname_prefix [if exp] [in range] [, statistic]

where statistic is one of

xb the linear prediction for each equation; the default. stdp the standard error of the linear predictions for each equation. pmarg the marginal success probability for each equation. pall the joint probabilities: (i) Pr(depvar_i = 1, all i) and (ii) Pr(depvar_i = 0, all i), for equations i = 1,...,M.

These statistics are available both in and out of sample; type "predict ... if e(sample) ..." if wanted only for the estimation sample. If no statistic is specified, the default is xb.

Description

mvppred provides predictions following estimation of an M-equation probit model by the method of simulated maximum likelihood (SML) using the program mvp7. See mvp7. Predictions provided for each equation are the fitted index values, the standard errors of the fitted index values for each equation, the predicted marginal success probabilities, and two predicted joint probabilities. These are: (i) Pr(depvar_i = 1, all i) and (ii) Pr(depvar_i = 0, all i), for equations i = 1,...,M. (Additional joint probabilities and conditional probabilities have not been provided because the number of such probabilities increases substantially as M increases.) The multivariate normal distributions used to calculate the joint probabilities are derived by simulation using the GHK simulator, with the seed and number of random draws the same as used by mvp7 to derive the parameter estimates.

Options

xb, the default, calculates the linear prediction (Xb) for each equation. Results are stored in the variables newvarname_prefixi, for equations i = 1,...,M.

stdp calculates the standard error of the linear prediction (Xb) for each equation. Results are stored in the variables newvarname_prefixi, for equations i = 1,...,M.

pmarg calculates the marginal probit predicted probability of success for each outcome, Pr(depvari) = 1, for each equation i = 1,...,M. Results are stored in the variables newvarname_prefixi, for equations i = 1,...,M.

pall calculates (i) the probit predicted joint probability of success in every outcome, Pr(depvari) = 1, for all i = 1,...,M, and (ii) the probit joint probability of failure in every outcome, Pr(depvari) = 0, for all i = 1,...,M. Results are stored in the variables newvarname_prefix1s for predicted probability (i) and newvarname_prefix0s for predicted probability (ii).

Examples

. use http://www.stata-press.com/data/r7/school.dta, clear

. mvp7 (private = years logptax loginc) (vote = years logptax loginc)

. mvppred xb

. mvppred pall, pall

. mvppred pmarg, pmarg

. mvppred stdp, stdp

. sum xb1, xb2, pmarg1, pmarg2, stdp1, stdp2, pall1s pall0s

Authors

Lorenzo Cappellari, Universita del Piemonte-Orientale, Italy <Lorenzo.Cappellari@eco.unipmn.it>

Stephen P. Jenkins, ISER, University of Essex, U.K. <stephenj@essex.ac.uk>

Also see

Manual: [U] 23 Estimation and post-estimation commands, [U] 29 Overview of model estimation in Stata,

On-line: help for mvp7, postest, and predict.