We discover: (a) in the low income group, there exists no causal relationship between energy consumption and economic growth; (b) in the. The purpose of this paper is to investigate the causal relationship between directional causality that runs from energy consumption to economic growth, whi. Afterwards, the causal relationship between energy consumption and economic growth is tested and ascertained. We discover: (a) in the low.
As mentioned previously, these results represent bidirectional causality, because when long-run relationships are estimated using cointegration tests, the magnitude positive or negative of the coefficients represents the direction of the causality Granger, ; Engle and Granger, For example, Lee and Chang explore the direction of causality between energy consumption and GDP through a dynamic panel in a sample of developed and developing countries.
Panel cointegration slope estimates long-run elasticities On a per-country basis, the cointegration results show that for all countries the slopes have a positive sign and are statistically significant. In other words, energy consumption has a positive impact on GDP.
In the cases of Argentina, Brazil and Chile, energy consumption exerts a positive and elastic effect on real GDP, whereas in the cases of Colombia and Paraguay energy consumption has a positive but smaller effect on real GDP. Regarding the relationship between real GDP and energy consumption, these findings show that for all countries, GDP has a positive effect on energy consumption.
This result demonstrates compliance with the feedback hypothesis, which holds that there is a bidirectional relationship between these two variables. Other studies such as Narayan et al. Table 9 presents these authors' results. We observe that the results of Narayan et al.
However, our results differ from the estimates shown in Table 9particularly for Colombia, but these results are not statistically significant. Finally, the results of Lee are similar to our estimates, but differ in the case of Venezuela.
Other results of long-run elasticities The results shown in Table 8 can be understood by analyzing the evolution of productive economic structures of South American countries, i. Table 10 shows the value added for each sector of the economy as a percentage of GDP for the 10 countries included in the study.
We can see that in recent decades the primary sector represents a smaller share of a nation's GDP and that secondary and tertiary sectors represent larger GDP shares. Argentina, Brazil and Chile have the largest elasticities reported in Table 8. This signifies that these countries' economies are goods-intensive in the secondary and tertiary sectors industry and services.
In the cases of Paraguay and Colombia, countries with lower elasticities, we can see that during the s and the past decade, both countries reduced the share of their primary sectors and increased participation of their tertiary sectors.
Value added by economy sector In particular, Table 10 demonstrates that countries with a high GDP share generated in the primary sector in relative terms in the s and a low share in the s should have low elasticities in the relationship between energy consumption and GDP. Conversely, countries whose GDP share from the primary sector has declined significantly should show high elasticities in the relationship between energy consumption and GDP. One exception to this behavior is Argentina, which saw a small change in relative terms.
Our evidence reflects the existence of panel stationarity for Latin American countries, and our panel attests to bidirectional causality between energy consumption and GDP in all sample countries. The literature investigates the impact of energy consumption on GDP for many countries using different techniques and methodologies. The results of these studies show that different methodologies lead to confusing and contradictory conclusions about this relationship. This paper estimates the elasticity of the long-run relationship of energy consumption-GDP and GDP-energy consumption for 10 countries in Latin America during the period from to We employ Pedroni'spanel cointegration test to determine if a long-run relationship exists between the variables in equations 1 and 2.
By using a cointegration test for panel data developed by Westerlundwhich accounts for possible cross-sectional dependence between countries and any existing structural breaks in the long-run relationship, we identify the long-run elasticities.
In the sections above, we provide empirical evidence about policy maker's abilities to design and implement programs to promote energy conservation and efficiency. In this case, because there is a long-run relationship between energy consumption and GDP, it is understood that in the long run energy generates economic growth for Latin American countries. In the cases of Bolivia, Colombia, Ecuador, Paraguay and even Peru and Uruguay, the elasticity of energy consumption is low below the regional average.
In these countries, policy makers could implement energy conservation programs with low negative impacts in the short run. However, if there is truth to the feedback hypothesis, which suggests that energy consumption and GDP are interrelated and complementary over time in a bidirectional, causal relationship, then policies that promote the energy efficiency do not negatively affect GDP. In addition, according to the results of our panel stationarity tests, if shocks in energy consumption and GDP are temporary, stabilization policies will power long-lasting effects in the countries of Latin America.
Finally, the result of our cointegration test suggests that energy consumption and GDP are endogenous variables in Latin American countries at the rate of the bidirectionality of causality.
Causality Relationship between Energy Consumption and Economic Growth in Brazil
Another interesting result is that the methodology is better than those used previously, in the sense that it reflects the presence of structural breaks, controls endogeneity and includes the presence of cross-correlation between the countries concerned. Countries such as Argentina, Brazil and Chile are energy-dependent, which means that policies that seek to conserve energy in the long run would have disastrous results on their economic growth.
Additionally, this dependence on the part of some Latin American countries indicates the need to diversify energy sources, since those countries must weigh the need for sustainable economic growth against the environmental costs associated with excessive energy consumption. Although it is difficult to make definitive conclusions about the energy policy of Latin American countries based on the empirical results presented in this paper, these findings serve to explain certain tools that can be used in conjunction with other studies in the decision-making process.
Future research could include variables such as physical capital, human capital and labor to estimate the long-run elasticities, following the methods of Mankiw, Romer and Weil This procedure would account for the fact that these factors of production are just as important as energy consumption. In addition, future research could extend the analysis to short-term relationships with a VEC model, as this model provides evidence that the series are cointegrated.
Additionally, future research could evaluate energy efficiency policies not on the basis of energy conservation measures, but rather from the perspective of the efficiency of energy use in production processes.
Long"On the relationship between energy and GNP: A reexamination," Journal of Energy Development 5: Baghestani"New evidence on the causal relationship between U.
Perron"Computation and analysis of multiple structural change models," Journal ofApplied Econometrics HinckleyBootstrap methods and their application. Fuller"Distribution of the estimators for autoregressive time series with a unit root," Journal of the American Statistical Association Granger"Co-integration and error-correction: The co-integration test indicates a long-run equilibrium relationship between variables, and energy consumption appears to be real GDP elastic.
This elasticity suggests that energy consumption has a great positive influence on changes in income. The causality results from the error correction model reveal a unidirectional short-run causality from energy consumption to economic growth and a bidirectional strong causality between them. These findings suggest that Brazil should adopt a dual strategy of increasing investment in energy infrastructure, and stepping up energy conservation policies to reduce any unnecessary waste of energy, in order to avoid having a negative effect on economic growth by reducing energy consumption.
In contrast, energy conservation is expected to increase the efficient use of energy and, therefore, enhance economic growth. Introduction Energy is the foundation of economic development and constitutes one of the vital infrastructure investments in social development. Both economy and energy consumption in Brazil have been growing rapidly.
In the recent five yearsBrazil has experienced greater growth rates in both energy use 4. The Olympic Committee has chosen Brazil as the host country for the Olympic Games, highlighting the fact that Brazil is one of the future bright stars of the world.
Official energy projections for Brazil indicate a continuing increase in demand for energy, in the next two decades. There are numerous studies that deal with the causality relationship between energy consumption and economic growth. The findings from the studies vary not only across countries but also across methodologies for the same country.
In a summary of the literature on the causal relationship between energy consumption and economic growth, there is evidence to support bidirectional or unidirectional causality, or no causality, between energy consumption and economic growth.
Evidence in either direction will have a significant bearing on policy. If, for example, there is unidirectional causality running from economic growth to energy consumption, it could imply that energy conservation policies may be implemented with little or no adverse effect on economic growth. Unidirectional causality running from economic growth to energy consumption was revealed by Ghosh  for India, by Mozumder and Marathe  for Bangladesh, by Narayan and Smyth  for Australia, by Yoo  for Indonesia and Thailand, and by Chen et al.
Unidirectional causality running from energy consumption to economic growth was revealed by Shiu and Lam  and Yuan et al. On the other hand, if bidirectional causality is found, economic growth may demand more energy whereas more energy consumption may induce economic growth. Energy consumption and economic growth may complement each other and energy conservation measures may negatively affect economic growth.
In addition, Chen et al. Finally, no causality in either direction would indicate that energy conservation policies may not affect economic growth, and rise in real income may not affect electricity consumption.
The purpose of this study is to investigate the causality relationship between energy consumption and economic growth, and to obtain policy implications from the results in Brazil. This purpose is accomplished by the following steps: First, stationarity and co-integration are tested; second, error-correction models are estimated to test for the Granger causality; finally, the F-tests are performed to determine the joint significance levels of causality between the two variables.
The remainder of this paper is organized as follows: Section 2 outlines the model and methodology. Section 3 discusses the data and empirical findings. The final section summarizes and concludes the paper. For modeling purposes, all of the data were converted into natural logarithms prior to conducting the empirical analysis. Thus, the series can be interpreted in growth terms after taking the first difference into account.
Model and Methodology 2. Model Following the empirical literature in energy economics, it is plausible to form a long-run relationship between energy consumption and economic growth in linear logarithm form, as follows: The error term, ut, is assumed to be independent and identically distributed with a zero mean and a constant variance.
The long-run income elasticity is given by: Econometric Methodology The empirical analysis tests for the existence of a long-term relationship between the variables in Equation 1 while using the vector error-correction model to capture the Granger causality between variables. A three-step procedure is performed. First, we check the integration order of each variable, since various co-integration tests are only valid if the variables have the same order of integration.
In terms of literature, tests designed on the basis of the null hypothesis that a series is I 1 have a low power of rejecting the null. Second, when all of the series of the same order are integrated, the Johansen maximum likelihood method  is used to test the co-integration relationship between the variables in Equation 1.
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If co-integration exists among the variables, OLS applied to estimate Equation 1 does not lead to a spurious regression result. Furthermore, the parameters estimated by OLS are super-consistent . The existence of co-integration indicates that there are long-run equilibrium relationships between the variables, and thereby, Granger causality exists between them in at least one direction  .
Finally, if all of the variables are I 1 and co-integrated, the error correction model ECM is used for correcting any disequilibrium in the co-integration relationship, captured by the error-correction term ECTas well as testing for long-run and short-run causality among the co-integrated variables. The ECM for Equation 1 is specified as follows: The negative sign of the estimated speed of adjustment coefficient is in accord with the convergence toward long run equilibrium .
The ECM represented by Equation 3 includes both the dependent variables with their own lags and the previous disequilibrium in terms of ECTt This specification can test the short-run and long-run causality among co-integrated variables.
Energy consumption is measured in BTU British thermal unit. Table 1 displays the summary statistics associated with the two variables. Figure 1 shows the change trend of each series for Brazil, all of which have increased across time. The energy consumption than the real GDP has exhibited a larger coefficient of variation CV shown in Table1 Table 2 shows average percentage growth rates in the years to of each series.
Fifteen-year, ten-year, and fiveyear growth rates are calculated as the growth between andandand andrespectively. In the most recent five yearsBrazil has experienced a greater growth rates in both energy use 4. For the time period between andthe energy consumption-income relationship Figure 2 shows a monotonic increase in Brazil. Therefore, Equation 1 is employed to examine how the energy consumption and economic growth are related in the long-run. Both the values of adjusted R2 and Jarque and Bera JB statistic  shown in Table 3 indicate Equation 1 is appropriate to test whether the two series are co-integrated.
All of the series appear to contain a unit root in their levels but are stationary in their first differ- a Figure 1. Time series plots of the energy consumption and real GDP, Summary statistics for Brazil, Average growth rates in percentages to for each variable.