Electricity consumption and real GDP causality nexus: Evidence from ARDL bounds testing approach for 11 MENA countries
TL;DR: In this article, the authors investigated the short-run and long-run causality issues between electricity consumption and economic growth in the selected 11 Middle East and North Africa (MENA) countries by using ARDL bounds testing approach of cointegration and vector error-correction models.
About: This article is published in Applied Energy.The article was published on 2011-08-01. It has received 274 citations till now. The article focuses on the topics: Cointegration.
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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
Cites methods from "Electricity consumption and real GD..."
...Therefore, following Ozturk and Acaravci (2011), we include a dummy variable in the ARDL model for India and we conduct again the corresponding CUSUM and CUSUMQ tests (Figure 3)....
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TL;DR: In this paper, the authors examined the empirical effects of economic growth, electricity consumption, foreign direct investment (FDI), and financial development on carbon dioxide (CO2) emissions in Kuwait using time series data for the period 1980-2013.
Abstract: This study examined the empirical effects of economic growth, electricity consumption, foreign direct investment (FDI), and financial development on carbon dioxide (CO2) emissions in Kuwait using time series data for the period 1980–2013. To achieve this goal, we applied the autoregressive distributed lag (ARDL) bounds testing approach and found that cointegration exists among the series. Findings indicate that economic growth, electricity consumption, and FDI stimulate CO2 emissions in both the short and long run. The VECM Granger causality analysis revealed that FDI, economic growth, and electricity consumption strongly Granger-cause CO2 emissions. Based on these findings, the study recommends that Kuwait reduce emissions by expanding its existing Carbon Capture, Utilization, and Storage plants; capitalizing on its vast solar and wind energy; reducing high subsidies of the residential electricity scheme; and aggressively investing in energy research to build expertise for achieving electricity generation efficiency.
486 citations
Cites background from "Electricity consumption and real GD..."
...…time series and panel studies have examined such associations (e.g., Begum et al., 2015; Salahuddin et al., 2015; Omri et al., 2014; Ozcan, 2013; Ozturk & Acaravci, 2011), to the best of the authors’ knowledge, no study has yet been undertaken to determine such causal relationships in the…...
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...Ozturk and Acaravci (2011) addressed short- and long-term causality issues between electricity consumption and economic growth in 11 Middle East and North African (MENA) countries using annual data for the period 1971-2006....
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TL;DR: In this article, the authors investigated the causes of carbon emissions by taking into account the role of financial development and economic growth in GCC countries, and found a long-run unidirectional causality running from carbon emissions to energy use in the case of Saudi Arabia, UAE, and Qatar.
Abstract: This study investigates the dynamic causal relationships among carbon emissions, financial development, economic growth, and energy consumption for Gulf Cooperation Council (GCC) countries from 1980 through 2011. Annual time series data and an autoregressive distributed lag (ARDL) model are used. The main contribution of this paper is that it has investigated the causes of carbon emissions by taking into account the role of financial development and economic growth in GCC countries. The results suggest long-run and causal relationships among carbon emissions, financial development, gross domestic product (GDP), and energy use in all GCC countries except United Arab Emirates (UAE). Moreover, there is long-run unidirectional causality running from carbon emissions to energy use in the case of Saudi Arabia, UAE, and Qatar. Furthermore, a one-way causal relationship from financial development to carbon emissions in the context of UAE, Oman, and Kuwait is found. The evidence suggests that financial systems should take into account environmental aspects in their current operations in these countries. The results of this study may be of great importance for policy and decision makers in developing energy policies for GCC countries that contribute to curbing carbon emissions while preserving economic growth.
410 citations
TL;DR: In this paper, the relative performance of renewable and non-renewable energy consumption on economic growth in 17 emerging economies was investigated using with bootstrap panel causality that allows both cross-section dependency and country specific heterogeneity across countries.
314 citations
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TL;DR: In this paper, 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.
311 citations
References
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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 paper, the authors consider a nonstationary vector autoregressive process which is integrated of order 1, and generated by i.i.d. Gaussian errors, and derive the maximum likelihood estimator of the space of cointegration vectors and the likelihood ratio test of the hypothesis that it has a given number of dimensions.
16,189 citations
"Electricity consumption and real GD..." refers methods in this paper
...The ARDL cointegration approach has numerous advantages in comparison with other cointegration methods such as Engle and Granger [21], Johansen [22], and Johansen and Juselius [23] procedures: First, the ARDL procedure can be applied whether the regressors are I(1) and/or I(0), while Johansen cointe-...
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TL;DR: In this paper, the authors developed a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend- or first-difference stationary.
Abstract: This paper develops a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend- or first-difference stationary. The proposed tests are based on standard F- and t-statistics used to test the significance of the lagged levels of the variables in a univariate equilibrium correction mechanism. The asymptotic distributions of these statistics are non-standard under the null hypothesis that there exists no level relationship, irrespective of whether the regressors are I(0) or I(1). Two sets of asymptotic critical values are provided: one when all regressors are purely I(1) and the other if they are all purely I(0). These two sets of critical values provide a band covering all possible classifications of the regressors into purely I(0), purely I(1) or mutually cointegrated. Accordingly, various bounds testing procedures are proposed. It is shown that the proposed tests are consistent, and their asymptotic distribution under the null and suitably defined local alternatives are derived. The empirical relevance of the bounds procedures is demonstrated by a re-examination of the earnings equation included in the UK Treasury macroeconometric model. Copyright © 2001 John Wiley & Sons, Ltd.
13,898 citations
Additional excerpts
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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
"Electricity consumption and real GD..." refers methods in this paper
...The ARDL cointegration approach has numerous advantages in comparison with other cointegration methods such as Engle and Granger [21], Johansen [22], and Johansen and Juselius [23] procedures: First, the ARDL procedure can be applied whether the regressors are I(1) and/or I(0), while Johansen cointe-...
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01 Jan 2005
10,230 citations