We propose the relaxation algorithm as a simple and powerful method for simulating the transition process in growth models. This method has a number of important advantages: (1) It can easily deal with a wide range of dynamic systems including multi-dimensional systems with stable eigenvalues...

This article demonstrates the use of two approaches to parallelizing a Garch(1,1) calibration algorithm. The base serial implementation is a genetic algorithm that uses maximum likelihood in the fitness function. This is written in generic C. The first type of parallelization involves...

We compare three alternative Maximum Likelihood Multidimensional Scaling methods for pairwise dissimilarity ratings, namely MULTISCALE, MAXSCAL, and gurations very well. The recovery of the true dimensionality depends on the test criterion (likelihood ratio test, AIC, or CAIC), as well as on the...

The classical canonical correlation analysis is extremely greedy to maximize the squared correlation between two sets of variables. As a result, if one of the variables in the dataset-1 is very highly correlated with another variable in the dataset-2, the canonical correlation will be very high...

We propose a new methodology for structural estimation of infinite horizon dynamic discrete choice models. We combine the Dynamic Programming (DP) solution algorithm with the Bayesian Markov Chain Monte Carlo algorithm into a single algorithm that solves the DP problem and estimates the...

In the economics of joint production one often distinguishes between the two cases: the one in which a firm produces multiple products each produced under separate production process, and the other "true joint production" where a number of outputs are produced from a single production process,...

This paper demonstrates how Goal Programming/Constrained Regression can be used for cross-checking results from standard econometric models as well as a stand alone methodology in empirical production analysis. For illustration, we re-examine Berndt and Wood's (BW) seminal study of the U.S....

In the Self Sufficiency Program (SSP) welfare demonstration, members of a randomly assigned treatment group could receive a subsidy for full time work. The subsidy was available for three years, but only to people who began working full time within 12 months of random assignment. A simple...

The least squares estimator is probably the most frequently used estimation method in regression analysis. Unfortunately, it is also quite sensitive to data contamination and model misspecification. Although there are several robust estimators designed for parametric regression models that can...

New methods for solving general linear parabolic partial differential equations (PDEs) in one space dimension are developed. The methods combine quadratic-spline collocation for the space discretization and classical finite differences, such as Crank-Nicolson, for the time discretization. The...