Journal ArticleDOI
Modeling and forecasting the CO2 emissions, energy consumption, and economic growth in Brazil
Hsiao-Tien Pao,Chung Ming Tsai +1 more
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In this article, the authors examined the dynamic relationship between pollutant emissions, energy consumption, and the output for Brazil during 1980-2007 and applied the Grey prediction model (GM) to predict three variables during 2008-2013.About:
This article is published in Energy.The article was published on 2011-05-01. It has received 484 citations till now. The article focuses on the topics: Energy consumption & Energy conservation.read more
Citations
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Causality Relationship between Energy Consumption and Economic Growth in Brazil
TL;DR: In this article, the authors investigated the relationship between energy consumption and economic growth in Brazil during the period of 1980-2008 and found that energy consumption has a great positive influence on changes in income.
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Greenhouse gas emission prediction on road network using deep sequence learning
TL;DR: In this paper, a deep learning framework was developed to predict link-level GHG emission rate (in CO 2 eq gram/second) based on the most representative predictors, such as speed, density, and GHG ER of previous time steps.
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Exploring the industrial solid wastes management system: Empirical analysis of forecasting and safeguard mechanisms.
TL;DR: Forecasting results show that China's ISWs generated have been a slowly increasing trend from 2018 to 2025, which will be controlled between 389819 million tons and 488002 million tons, and the utilization, disposal and storage of ISWs have a significant upward trend.
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Energy-related CO2 emission forecast for Turkey and Europe and Eurasia: A discrete grey model approach
TL;DR: In this article, the authors used discrete grey models (DGMs) to predict the energy-related CO2 emissions in Turkey and total Europe and Eurasia region from 2015 to 2030 using data set between 1965 and 2014.
References
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Journal ArticleDOI
Co-integration and Error Correction: Representation, Estimation and Testing
TL;DR: The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples.
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Testing for a Unit Root in Time Series Regression
TL;DR: In this article, the authors proposed new tests for detecting the presence of a unit root in quite general time series models, which accommodate models with a fitted drift and a time trend so that they may be used to discriminate between unit root nonstationarity and stationarity about a deterministic trend.
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Likelihood ratio statistics for autoregressive time series with a unit root
David A. Dickey,Wayne A. Fuller +1 more
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Maximum likelihood estimation and inference on cointegration — with applications to the demand for money
Søren Johansen,Katarina Juselius +1 more
TL;DR: In this paper, the estimation and testing of long-run relations in economic modeling are addressed, starting with a vector autoregressive (VAR) model, the hypothesis of cointegration is formulated as a hypothesis of reduced rank of the long run impact matrix.