Renewable energy, non-renewable energy and economic growth in Brazil
TL;DR: In this paper, the authors explored the causal relationship between real GDP and four types of energy consumption: NHREC, total renewable energy consumption (TREC), non-renewable energy consumption, and the total primary energy consumption.
Abstract: This study employs Brazil’s yearly statistics from 1980 to 2010 to explore the causal relationships between the real GDP and four types of energy consumption: non-hydroelectric renewable energy consumption (NHREC), total renewable energy consumption (TREC), non-renewable energy consumption (NREC), and the total primary energy consumption (TEC). The cointegration test reveals a long-run equilibrium among Brazil’s real GDP, labour, capital, and each of the four types of consumption. The development of the Brazilian economy has close ties with capital formation and labour force. The influence of NHREC/TREC on real output is positive and significant, while the impacts by NREC/TEC are insignificant. The results from the vector error correction models reveal a unidirectional causality from NHREC to economic growth, a bidirectional causality between economic growth and TREC, and a unidirectional causality from economic growth to NREC or TEC without feedback in the long-run. These findings suggest that Brazil is an energy-independent economy and that economic growth is crucial in providing the necessary resources for sustainable development. Expanding renewable energy would not only enhance Brazil’s economic growth and curb the deterioration of the environment but also create an opportunity for a leadership role in the international system and improve Brazil’s competition with more developed countries.
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TL;DR: In this article, the causal relationship between economic growth and renewable energy consumption in BRICS countries over the period 1971-2010 within a multivariate framework was investigated, based on the ARDL estimates, there exist long-run equilibrium relationships among the competing variables.
Abstract: The current study investigates the causal relationship between economic growth and renewable energy consumption in the BRICS countries over the period 1971–2010 within a multivariate framework. The ARDL bounds testing approach to cointegration and vector error correction model (VECM) are used to examine the long-run and causal relationships between economic growth, renewable energy consumption, trade openness and carbon dioxide emissions. Empirical evidence shows that, based on the ARDL estimates, there exist long-run equilibrium relationships among the competing variables. Regarding the VECM results, bi-directional Granger causality exists between economic growth and renewable energy consumption, suggesting the feedback hypothesis, which can explain the role of renewable energy in stimulating economic growth in BRICS countries.
494 citations
TL;DR: In this article, the authors examined the renewable energy consumption and economic growth causality nexus in Turkey, and the results of this country-specific study support conservation hypothesis, and they showed that there is a unidirectional causality running from economic growth to renewable consumption.
Abstract: This paper examines the renewable energy consumption–economic growth causality nexus in Turkey. Studies in the literature can be grouped as country-specific and multi-country studies. The results of these studies are inconsistent, and there is no agreement on the existence or the direction of causality between renewable energy consumption and economic growth. The results of this country-specific study support conservation hypothesis. The results of empirical tests from ARDL approach show that renewable energy consumption has a negative impact on economic growth, and the ones of Toda–Yamamoto causality tests show that there is a unidirectional causality running from economic growth to renewable energy consumption.
443 citations
TL;DR: In this paper, the authors investigated the relationship between renewable energy consumption and economic growth in China for the period 1977-2011 and found that there is a bi-directional long-term causality between renewables consumption and the economic growth.
Abstract: The aim of this paper is to investigate the relationship between renewable energy consumption and economic growth in China for the period 1977–2011. Autoregressive Distributed Lag approach (ARDL) to cointegration and Johansen cointegration techniques are employed by including intermittent variables namely carbon dioxide emissions and labor. We also employed Granger causality test in order to determine the direction of the causality among the variables. The results show that there is a bi-directional long term causality between renewable energy consumption and economic growth. This finding implies that growing economy in China is propitious for the development of renewable energy sector which in turn helps to boost economic growth. We also find that labor influences renewable energy consumption in the short term. However, there is no evidence of long or short run causality between carbon emissions and renewable energy consumption. This implies that actual level of renewable energy in China is still insignificant and not considerably exploited in order to contribute to the mitigation of carbon dioxide emissions.
375 citations
TL;DR: In this paper, the authors investigated the long-term output elasticities between renewable energy consumption and non-renewable energy consumption in Asia-pacific economic cooperation (APEC) countries.
352 citations
TL;DR: In this paper, an exhaustive survey of the literature related to the energy-environment-growth nexus at the individual and regional scale studies covering the period from 1978 to 2014 is presented, which is based on the causality direction among energy use variables (electricity, nuclear, renewable and non-renewable) and output growth; between economic growth and environment; and between the three variables at the same time.
Abstract: The aim of this study is to exhibit an exhaustive survey which is related to the great flight of the literature of energy- environment-growth nexus at the individual and regional scale studies covering the period from 1978 to 2014. The survey takes into consideration the sample (country, region, etc.), periods covering, econometric strategies, and conclusions. Our survey is based on the causality direction among (i) the energy use variables (electricity, nuclear, renewable and non-renewable) and output growth; (ii) between economic growth and environment; and between the three variables at the same time. Globally, these surveys provide paradoxical and not conclusive results which energy consumption can boost economic growth through the productivity enhancement and it can boost also the environmental damages through the enhancement of pollutant emissions. Our survey sheds more the lights on the energy-environment-growth literature by giving an extensive listing (1978–2014) of these causal linkages among the energy use variables, environment and economic growth for both individual and collective cases. There is a unanimous consensus about the importance of dealing with such dynamic relationship, which is seems to be a cornerstone element in setting any ambition strategies (energy, ecological and economics).
312 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
"Renewable energy, non-renewable ene..." refers methods in this paper
...Three different unit root tests, namely Augmented Dickey–Fuller (ADF) [31], the Phillips–Perron (PP) [32] and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) [33] are used to investigate the stationarity and the order of the integration of the variables....
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13,292 citations
"Renewable energy, non-renewable ene..." refers methods in this paper
...(2) are evaluated through three different unit root tests, namely ADF, PP, and KPSS....
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...Hence, KPSS is sometimes used to complement the widely used ADF and PP tests to obtain robust results....
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...Three different unit root tests, namely Augmented Dickey–Fuller (ADF) [31], the Phillips–Perron (PP) [32] and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) [33] are used to investigate the stationarity and the order of the integration of the variables....
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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