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https://hdl.handle.net/10419/33466
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cappellari, Lorenzo | en |
dc.contributor.author | Jenkins, Stephen P. | en |
dc.date.accessioned | 2006-11-15 | - |
dc.date.accessioned | 2010-07-07T09:12:01Z | - |
dc.date.available | 2010-07-07T09:12:01Z | - |
dc.date.issued | 2006 | - |
dc.identifier.uri | http://hdl.handle.net/10419/33466 | - |
dc.description.abstract | We 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 |
dc.language.iso | eng | en |
dc.publisher | |aInstitute for the Study of Labor (IZA) |cBonn | en |
dc.relation.ispartofseries | |aIZA Discussion Papers |x2112 | en |
dc.subject.jel | C15 | en |
dc.subject.jel | C51 | en |
dc.subject.jel | C87 | en |
dc.subject.ddc | 330 | en |
dc.subject.keyword | simulation estimation | en |
dc.subject.keyword | maximum simulated likelihood | en |
dc.subject.keyword | multivariate probit | en |
dc.subject.keyword | Halton sequences | en |
dc.subject.keyword | pseudo-random sequences | en |
dc.subject.keyword | multivariate normal | en |
dc.subject.keyword | GHK simulator | en |
dc.title | Calculation of multivariate normal probabilities by simulation, with applications to maximum simulated likelihood estimation | - |
dc.type | |aWorking Paper | en |
dc.identifier.ppn | 51162882X | en |
dc.rights | http://www.econstor.eu/dspace/Nutzungsbedingungen | en |
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