The Influence of Macroeconomics Predictors, Urbanization, and Biomass Consumption on Carbon Emission in Asia using Spatial Regression Method

Saputri, Rizka Yuliani (2023) The Influence of Macroeconomics Predictors, Urbanization, and Biomass Consumption on Carbon Emission in Asia using Spatial Regression Method. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Global warming is an environmental problem that affects every country in the world. The earth's temperature is increasing caused by the trapped of geothermal heat by greenhouse gas emissions. Greenhouse gases, especially carbon dioxide emissions, are viewed as one of the core causes of environmental degradation. The amount of carbon emission is strongly influenced by economic growth according to the Environmental Kuznets Curve (EKC) hypothesis. This research aims to know the influence of macroeconomic predictors, urbanization, and biomass consumption on carbon emissions in Asia with spatial effects in the model. This research used spatial regressions, namely the Spatial Autoregressive Model (SAR) and Spatial Error Model (SEM). The predictor variables using Gross Domestic Product (GDP) per capita, Trade, Urbanization, and Biomass Consumption and carbon emissions as response variables from 2019 in Asia. This research also discussed multiple linear regression and spatial regression using Principal Component Analysis (PCA) and backward elimination with a significance level of 10%. According to the result PCA, the first two components explain 80.2% of the variation in the data. Therefore, for this research, using m=2. The best method between PCA and without PCA for Multiple Linear Regression, SAR, and SEM is SAR without PCA or SAR with all predictors. Then using backward elimination, the best of SAR model is obtained with good R^2 adjusted. The significant variables in the SAR model are GDP per capita and Urbanization variables.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Carbon Emission, Macroeconomics, Urbanization, Biomass Consumption, Spatial Regression
Subjects:	H Social Sciences > HA Statistics > HA30.6 Spatial analysis
Divisions:	Faculty of Mathematics, Computation, and Data Science > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Rizka Yuliani Saputri
Date Deposited:	09 Sep 2024 02:21
Last Modified:	09 Sep 2024 02:21
URI:	http://repository.its.ac.id/id/eprint/104615

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