Modeling and forecasting the CO2 emissions, energy consumption, and economic growth in Brazil
TL;DR: 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.
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TL;DR: In this article, the authors examined the linkages among economic growth, energy consumption, financial development, trade openness and CO2 emissions over the period of 1975Q1-2011Q4 in the case of Indonesia.
Abstract: This study examines the linkages among economic growth, energy consumption, financial development, trade openness and CO2 emissions over the period of 1975Q1-2011Q4 in the case of Indonesia. The stationary analysis is performed by using Zivot-Andrews structural break unit root test and the ARDL bounds testing approach for a long run relationship between the series in the presence of structural breaks. The causal relation between the concerned variable is examined by the VECM Granger causality technique and robustness of causal analysis is tested by innovative accounting approach (IAA). Our results confirm that the variables are cointegrated; it means that the long run relationship exists in the presence of structural break stemming in the series. The empirical findings indicate that economic growth and energy consumption increases CO2 emissions, while financial development and trade openness compact it. The VECM causality analysis has shown the feedback hypothesis between energy consumption and CO2 emissions. Economic growth and CO2 emissions are also interrelated i.e. bidirectional causality. Financial development Granger causes CO2 emissions. The study opens up a new policy insights to control the environment from degradation by using energy efficient technologies. Financial development and trade openness can also play their role in improving the environmental quality.
1,020 citations
TL;DR: In this paper an attempt is made to review the various energy demand forecasting models to accurately predict the future energy needs.
Abstract: Energy is vital for sustainable development of any nation – be it social, economic or environment. In the past decade energy consumption has increased exponentially globally. Energy management is crucial for the future economic prosperity and environmental security. Energy is linked to industrial production, agricultural output, health, access to water, population, education, quality of life, etc. Energy demand management is required for proper allocation of the available resources. During the last decade several new techniques are being used for energy demand management to accurately predict the future energy needs. In this paper an attempt is made to review the various energy demand forecasting models. Traditional methods such as time series, regression, econometric, ARIMA as well as soft computing techniques such as fuzzy logic, genetic algorithm, and neural networks are being extensively used for demand side management. Support vector regression, ant colony and particle swarm optimization are new techniques being adopted for energy demand forecasting. Bottom up models such as MARKAL and LEAP are also being used at the national and regional level for energy demand management.
1,002 citations
TL;DR: In this article, the authors tried to establish a long-run as well as causal relationship between economic growth and carbon dioxide (CO2) emissions for Malaysia using data for the years from 1980 to 2009, the Environmental Kuznets Curve hypothesis was tested utilizing the Auto Regressive Distributed Lag (ARDL) methodology.
627 citations
TL;DR: In this article, the authors investigated the existence of the environmental Kuznets curve (EKC) hypothesis in Vietnam during the period 1981-2011 and established a pollution model by applying the Autoregressive Distributed Lag (ARDL) methodology.
622 citations
TL;DR: In this article, the authors investigated the environmental Kuznets curve (EKC) hypothesis using a country's ecological footprint as an indicator of environmental degradation, and the results showed an inverted U-shaped relationship between the ecological footprint and GDP growth, which represents the EKC hypothesis in upper middle and high income countries but not in low- and lower middle-income countries.
540 citations
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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.
Abstract: 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. If each element of a vector of time series x first achieves stationarity after differencing, but a linear combination a'x is already stationary, the time series x are said to be co-integrated with co-integrating vector a. There may be several such co-integrating vectors so that a becomes a matrix. Interpreting a'x,= 0 as a long run equilibrium, co-integration implies that deviations from equilibrium are stationary, with finite variance, even though the series themselves are nonstationary and have infinite variance. The paper presents a representation theorem based on Granger (1983), which connects the moving average, autoregressive, and error correction representations for co-integrated systems. A vector autoregression in differenced variables is incompatible with these representations. Estimation of these models is discussed and a simple but asymptotically efficient two-step estimator is proposed. Testing for co-integration combines the problems of unit root tests and tests with parameters unidentified under the null. Seven statistics are formulated and analyzed. The critical values of these statistics are calculated based on a Monte Carlo simulation. Using these critical values, the power properties of the tests are examined and one test procedure is recommended for application. In a series of examples it is found that consumption and income are co-integrated, wages and prices are not, short and long interest rates are, and nominal GNP is co-integrated with M2, but not M1, M3, or aggregate liquid assets.
27,170 citations
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.
Abstract: SUMMARY This paper proposes new tests for detecting the presence of a unit root in quite general time series models. Our approach is nonparametric with respect to nuisance parameters and thereby allows for a very wide class of weakly dependent and possibly heterogeneously distributed data. The tests 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. The limiting distributions of the statistics are obtained under both the unit root null and a sequence of local alternatives. The latter noncentral distribution theory yields local asymptotic power functions for the tests and facilitates comparisons with alternative procedures due to Dickey & Fuller. Simulations are reported on the performance of the new tests in finite samples.
16,874 citations
13,292 citations
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.
Abstract: 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 the hypothesis of reduced rank of the long-run impact matrix. This is given in a simple parametric form that allows the application of the method of maximum likelihood and likelihood ratio tests. In this way, one can derive estimates and test statistics for the hypothesis of a given number of cointegration vectors, as well as estimates and tests for linear hypotheses about the cointegration vectors and their weights. The asymptotic inferences concerning the number of cointegrating vectors involve nonstandard distributions. Inference concerning linear restrictions on the cointegration vectors and their weights can be performed using the usual chi squared methods. In the case of linear restrictions on beta, a Wald test procedure is suggested. The proposed methods are illustrated by money demand data from the Danish and Finnish economies.
12,449 citations
01 Jan 2005
10,230 citations