
The Economic Development Impact To Environment Quality : Kuznet’s Curve Hyphothesis and Non Linier Regression Approach
Author(s) -
Rizka Zulfikar,
Farida Yulianti,
Teguh Wicaksono,
Prihatini Ade Mayvita
Publication year - 2021
Publication title -
international journal of science, technology and management
Language(s) - English
Resource type - Journals
ISSN - 2722-4015
DOI - 10.46729/ijstm.v2i3.205
Subject(s) - human development index , index (typography) , unemployment , poverty , economic indicator , agriculture , economics , descriptive statistics , quality (philosophy) , regression analysis , linear regression , econometrics , agricultural economics , geography , environmental science , natural resource economics , statistics , human development (humanity) , economic growth , mathematics , computer science , philosophy , archaeology , epistemology , world wide web , macroeconomics
This study aims was to identify impact of economic development factors to the the environment quality by using Kuznet's Curve Hyphotesis and non linear regression. The determinants studied are indicators of economic development such as Gross Domestic Regional Income (GDRI) of the industrial sector, mining sector, agricultural/plantation /forestry/fishery/livestock sectors, poverty, unemployment and human development index (HDI). While the environmental quality indicators used are Water Quality Index (WQI), Air Quality Index (AQI) and Land Cover Quality Index (LCQI). The data used is secondary data from the Department of Environment, the Department of Energy and Mineral Resources, and also the Central Bureau of Statistics of South Kalimantan Province. Secondary data types used include WQI, AQI, LCQI, GDRI, poverty, unemployment and HDI data for the period 2006 – 2020.
The method used in this study is descriptive quantitatively using Kuznet's Curve hypothesis and non linear regression. The final results obtained from this study include (1) The influence of economic development indicators on environmental quality is in accordance with Kuznet's Curve hypothesis and shows non-linear relationships. (2) Only the unemployment indicator is not identified non-linearly due to the adjusted value of R Square 0.05.