@TechReport{iza:izadps:dp2112,
            	author={Cappellari, Lorenzo and Jenkins, Stephen P.},
            	title={Calculation of Multivariate Normal Probabilities by Simulation, with Applications to Maximum Simulated Likelihood Estimation},
            	year={2006},
	month={May},
            	institution={Institute of Labor Economics (IZA)},
            	address={Bonn},
            	type={IZA Discussion Paper},
            	number={2112},
            	url={https://www.iza.org/publications/dp2112},
	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.},
	keywords={pseudo-random sequences;simulation estimation;Halton sequences;multivariate probit;maximum simulated likelihood;multivariate normal;GHK simulator},
            }