Environmental quality index modeling in Indonesia using ordinal probit regression approach for panel data with random effect

• Published in: Journal of physics. Conference series 2019-07, Vol.1277 (1), p.12044
• Main Author: Suliyanto
• Format: Article
• Language: English
• Subjects: Air quality; Environment models; Environmental quality; Longitudinal studies; Parameter estimation; Physics; Population density; Quadratures; Regression models; Water quality
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/1277/1/012044

Environmental issues are one of the important global issues and are of concern because they are considered to require a solution. The Ministry of Environment and Forestry has developed an Environment Quality Index (EQI) that provides rapid information of an environmental condition with river water quality, air quality, and forest as indicator. This study aims to model EQI in Indonesia using ordinal probit regression for panel data with random effects. Parameter estimation of ordinal probit regression model for panel data with random effect using the marginal likelihood function, and maximize that function using M-point Gauss-Hermite Quadrature method. The data that be used in this study is EQI from 33 Provinces in Indonesia during 2011 to 2016 which are categorized into three category i.e less good, good and very good. The result of modelling is gotten variable that influence to EQI is Human Development Index (HDI). EQI opportunities in DKI Jakarta province in the year 2016 in the category of less good is high enough, that is equal to 99.89%. This may be due to high population density and less balanced with awareness of the population to preserve the environment. The accuracy of classification of modeling result is 70.202%.