The paper documents MINTOOLKIT for GNU Octave. MINTOOLKIT provides functions for minimization and numeric differentiation. The main algorithms are BFGS, LBFGS, and simulated annealing. Examples are given.

We explore the determinants of usage of six different types of health careservices, using the Medical Expenditure Panel Survey data, years 1996-2000.We apply a number of models for univariate count data, including semiparametric, semi-nonparametric and finite mixture models.We find that the...

This paper presents a cross validation method for selection of statistics for Approximate Bayesian Computing, and for related estimation methods such as the Method of Simulated Moments. The method uses simulated annealing to minimize the cross validation criterion over a combinatorial search...

Given a sample from a fully specified parametric model, let Zn be a given finite-dimensional statistic - for example, an initial estimator or a set of sample moments. We propose to (re-)estimate the parameters of the model by maximizing the likelihood of Zn. We call this the maximum indirect...

A graphical processing unit (GPU) is a hardware device normally used to manipulate computer memory for the display of images. GPU computing is the practice of using a GPU device for scientific or general purpose computations that are not necessarily related to the display of images. Many...

This is a guide that explains how to use software that implements the simulated nonparametric moments (SNM) estimator proposed by Creel and Kristensen (2009). The guide shows how results of that paper may easily be replicated, and explains how to install and use the software for estimation of...

Abstract. Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the...

Consider a model with parameter phi, and an auxiliary model with parameter theta. Let phi be a randomly sampled from a given density over the known parameter space. Monte Carlo methods can be used to draw simulated data and compute the corresponding estimate of theta, say theta_tilde. A large...

Abstract We re-examine the theoretical concept of a production function for cognitive achievement, and argue that an indirect production function that depends upon the variables that constrain parents' choices is both more tractable from an econometric point of view, and more interesting from an...

The parameterized expectations algorithm (PEA) involves a long simulationand a nonlinear least squares (NLS) fit, both embedded in a loop. Both steps are natural candidates for parallelization.This note shows that parallelization can lead to important speedups forthe PEA.I provide example code...