Comparison of Spatial Weight Matrices in Spatial Autoregressive Model: Case Study of Intangible Cultural Heritage in Indonesia

Abstract

Intangible Cultural Heritage (ICH) can effectively contribute to Sustainable Development Goals (SDGs) in all economic, social, and environmental dimensions, along with peace and security. Studying ICH in Indonesia cannot be separated from the spatial aspect of how an area's attributes are related to other areas located close to each other. Spatial regression modeling needs to be done by considering the selection of spatial weight matrix. Using the wrong spatial weight matrix will increase the standard error in parameter estimation. Therefore, this study aims to determine: the best spatial weight matrix to accommodate the spatial autocorrelation in analyzing the description of the spread of ICH in Indonesia; and the variables that are thought to influence the number of ICH determination in Indonesia. The spatial regression modeling used in this study is the Spatial Autoregressive (SAR) model and the spatial weight matrices compared in this study are queen contiguity and inverse distance. The best model is the SAR model used the queen contiguity spatial weight matrix because it has minimum values of AIC, BIC, RMSE and MAPE which are 310.397, 319.555, 18.857 and 57.169 respectively. Simultaneously, involved in performing arts, wearing traditional dress, knowing Indonesian folklore and the spatial lag contribute significantly to number of ICH determination in Indonesia. Partially, only knowing Indonesian folklore have a significant effect on number of ICH determination in Indonesia at significance level α=5%. Each additional 1% of population that knowing Indonesian folklore in an area increases number of ICH determination in that area by 0.6719 units .

Keywords

• intangible cultural heritage
• spatial autoregressive
• queen contiguity
• inverse distance