Monte carlo simulation of the multivariate spatial durbin model for complex data sets

Atikah, Nur, Widodo, Basuki, Mardlijah, Mardlijah, Rahardjo, Swasono, Harini, Sri and Dinnullah, Riski Nur Istiqomah (2024) Monte carlo simulation of the multivariate spatial durbin model for complex data sets. International Journal of Mathematics and Computer Science. ISSN 1814-0432

Text 20858.pdf Download (108kB)

Abstract

The Multivariate Spatial Durbin Model (MSDM) is a significant advance in spatial econometrics, very relevant in the context of research problems. This model extends spatial analysis by capturing the complexity and dynamism of interactions between variables in a spatial context that is often ignored by classical spatial models. Furthermore, this article aims to estimate the parameters of MSDM model applied to large and complex data sets through Monte Carlo simulations. This model was then estimated using Maximum Likelihood Estimation (MLE), and to test the accuracy of the model using the Maximum Likelihood Ratio Test (MLRT) with a computational approach. The research results show that the MSDM model parameter estimates are accurate as indicated by an accuracy value that is smaller than the 5% significance level. The model becomes more efficient as the sample size increases.

Item Type:	Journal Article
Keywords:	Multivariate Spatial Durbin Model, Monte Carlo Simulation, Maximum Likelihood Estimation; Maximum Likelihood Ratio Test; Complex Data Sets
Subjects:	01 MATHEMATICAL SCIENCES > 0104 Statistics > 010405 Statistical Theory
Divisions:	Faculty of Mathematics and Sciences > Department of Mathematics
Depositing User:	Prof SRI HARINI
Date Deposited:	28 Oct 2024 10:37

Downloads

Origin of downloads

Actions (login required)

View Item