Evaluating Simulation-based Approaches and Multivariate Quadrature on Sparse Grids in Estimating Multivariate Binary Probit Models

TY - JOUR

T1 - Evaluating Simulation-based Approaches and Multivariate Quadrature on Sparse Grids in Estimating Multivariate Binary Probit Models

AU - Abay, Kibrom Araya

N1 - JEL classification: C15, C25, C35

PY - 2015/1/1

Y1 - 2015/1/1

N2 - This paper evaluates the performance of a recently emerging multivariate quadrature-based Sparse Grids Integration (SGI) and the well-known Geweke-Hajivassiliou-Keane (GHK) simulator in estimating multivariate binary probit models. Monte Carlo exercises demonstrate that in lower dimension multivariate binary probit models, the multivariate quadrature-based SGI estimator with few quadrature points performs very well and comparable with the GHK simulator. But as the dimension of integration or dependence (error correlation) among equations increases, the GHK simulator outshines the SGI estimator. This indicates that for integration problems involving higher dimension multivariate probit models, and those with strong dependence among variables, the GHK simulator remains to be a more efficient approach.

AB - This paper evaluates the performance of a recently emerging multivariate quadrature-based Sparse Grids Integration (SGI) and the well-known Geweke-Hajivassiliou-Keane (GHK) simulator in estimating multivariate binary probit models. Monte Carlo exercises demonstrate that in lower dimension multivariate binary probit models, the multivariate quadrature-based SGI estimator with few quadrature points performs very well and comparable with the GHK simulator. But as the dimension of integration or dependence (error correlation) among equations increases, the GHK simulator outshines the SGI estimator. This indicates that for integration problems involving higher dimension multivariate probit models, and those with strong dependence among variables, the GHK simulator remains to be a more efficient approach.

U2 - 10.1016/j.econlet.2014.11.021

DO - 10.1016/j.econlet.2014.11.021

M3 - Journal article

SN - 0165-1765

VL - 126

SP - 51

EP - 56

JO - Economics Letters

JF - Economics Letters

ER -