mvtobit使用说明.docx

-------------------------------------------------------------------------------help for mvtobit Mikkel Barslund (mikkelbarslund@)-------------------------------------------------------------------------------Multivariate tobit models estimated by maximum simulated likelihood mvtobit equation1 equation2 ... equationM [weight] [if exp] [in range] [, draws(#) an seed(#) beta0 atrho0(matrix_name) prefix(string) burn(integer) random hrandom shuffle adoonly primes(matrix_name) init(matrix_name) robust cluster(varname) constraints(numlist) level(#) maximize_options ] where each equation is specified as ( [eqname:] depvar [=] [varlist] [, noconstant] ) by ... : may be used with mvtobit; see help by. pweights, fweights, aweights, and iweights are allowed; see help weights. mvtobit is likely to produce a series of (not concave) statements in the beginning of the estimation process. It is recommended to specify the difficult option; see help maximize. mvtobit shares the features of all estimation commands; see help est. mvtobit typed without arguments redisplays the last estimates. The level option may be used. mvtobit requires mdraws to be installed. Note: much code in this routine is hacked from or inspired by Cappellari and Jenkins mvprobit and mdraws commands (see mvprobit and mdraws if installed). This in particular applies to the help and syntax handling files. mdraws must be installed for mvtobit to work. The shuffle option requires installation of _gclsort. Both are available from SSC. Using Stata version 9 or above? Take a look at cmp and Roodman (2009).Description mvtobit estimates M-equation tobit models (including bivariate models), by the method of maximum simulated likelihood (MSL). Bivariate tobit models are estimated without simulation (see also Daniel Lawsons bitobit if installed). A limitation is that only models left-censored at zero can be estimated, i.e. y(i) = max[xb(i)+e(i),0] where e is M-variate normally distributed. Along with coefficients for each