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Fortran Programs

Bear paw An historical QUAIL archive (loaded Apr-01). The last time this code was run was in 1990 on a CDC. It would be very rare indeed to find that someone still has a functional CDC 6400 with a Fortran compiler capable of compiling this code! This is source code for QUAIL, release 4. QUAIL was developed by Daniel McFadden and a team of programmers at the University of California, Berkeley in the early 1970s, and is the ancestor of today's programs that do qualitative choice analysis (e.g., multinomial logit). We offer a zip archive or a tarfile for download, with the caveat, of course, that we cannot support the code.

Bear paw Keh-Shin Lii and Mark Lehr (loaded Jul-98). Source code for maximum likelihood estimates for non-gaussian ARMA models.

Bear paw A. Ronald Gallant and George Tauchen (linked Sep-97). Source code for efficient method of moments estimation.

Bear paw A. Ronald Gallant and George Tauchen (linked Sep-97. Source code for semi- and nonparametric time series analysis.

Bear paw William Goffe (loaded Aug-95). Source code for simulated annealing, a global optimization method that distinguishes between different local optima.

Bear paw Vassilis Hajivassiliou (linked Sep-95). Simulation routines for rectangle multivariate normal probabilities and derivatives.

Bear paw Vassilis Hajivassiliou and Axel Boersch-Supan (linked Sep-95). Link to smoothly simulated maximum likelihood Fortran code for the multinomial probit model.

Bear paw Axel Boersch-Supan (linked Sep-95).Link (mirror site) to Fortran code for hierarchical logit models. Available for PCs and Unix workstations. To obtain a copy of the program for a nominal fee, please contact Professor Boersch-Supan at axel@econ.uni-mannheim.de.

Bear paw James B. Davies, David A. Green, and Harry J. Paarsch (loaded Dec-95). Source code for computing the non-parametric estimates of the Lorenz curve ordinates for a sample of N independently and identically distributed draws concerning the random variable Y which has the population cumulative distribution function F(y).

Bear paw James B. Davies, David A. Green, and Harry J. Paarsch (loaded Dec-95). Source code for computing the non-parametric estimates of the generalized Lorenz curve.