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dc.contributor.authorCappellari, Lorenzoen_US
dc.contributor.authorJenkins, Stephen P.en_US
dc.description.abstractWe discuss methods for calculating multivariate normal probabilities by simulation and two new Stata programs for this purpose: -mdraws- for deriving draws from the standard uniform density using either Halton or pseudo-random sequences, and an egen function -mvnp()- for calculating the probabilities themselves. Several illustrations show how the programs may be used for maximum simulated likelihood estimation.en_US
dc.publisherInstitute for the Study of Labor (IZA) Bonnen_US
dc.relation.ispartofseriesIZA Discussion Papers 2112en_US
dc.subject.keywordsimulation estimationen_US
dc.subject.keywordmaximum simulated likelihooden_US
dc.subject.keywordmultivariate probiten_US
dc.subject.keywordHalton sequencesen_US
dc.subject.keywordpseudo-random sequencesen_US
dc.subject.keywordmultivariate normalen_US
dc.subject.keywordGHK simulatoren_US
dc.titleCalculation of multivariate normal probabilities by simulation, with applications to maximum simulated likelihood estimationen_US
dc.typeWorking Paperen_US
Appears in Collections:IZA Discussion Papers, Forschungsinstitut zur Zukunft der Arbeit (IZA)

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