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...

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 parameter....

The Hausman (1978) test is based on the vector of differences of two estimators. It is usually assumed that one of the estimators is fully efficient, since this simplifies calculation of the test statistic. However, this assumption limits the applicability of the test, since widely used...

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 shows how a high level matrix programming language may be used to perform Monte Carlo simulation, bootstrapping, estimation by maximum likelihood and GMM, and kernel regression in parallel on symmetric multiprocessor computers or clusters of workstations. The implementation of...

This document contains lecture notes for a first year graduate course in econometrics, with coverage of basic topics such as OLS and hypothesis testing, through maximum likelihood and GMM, nonlinear models, time series, panel data, Bayesian methods, simulation-based methods, and other topics....

PelicanHPC is a rapid (around 5 minutes, when you know what you're doing) means of setting up a high performance computing (HPC) cluster for parallel computing using MPI. This tutorial gives a basic description of what PelicanHPC does,  addresses how to use the released CD images to set up a...