Economic growth and energy consumption in Brazil c

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RESEARCH ARTICLE

Economic growth and energy consumption in Brazil: cointegration and causality analysis

Marco Mele¹

Received: 2 July 2019 / Accepted: 1 August 2019

#Springer-Verlag GmbH Germany, part of Springer Nature 2019

Abstract

Energy is a crucial part of any economy and holds a central position in enhancing social development in the world. Energy consumption and the economy in Brazil have both increased in the past decade. In this paper, time series statistics from 1980 to 2017 will be used to analyze the relationship between real GDP per capita and energy consumption to will examine how energy use in the country affects economic growth using causality models. This is established through testing for stationarity using Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test for trend stationarity. A cointegration relationship is found between the two variables.

Keywords Economic growth . Energy use . Brazil . Time series JEL classifications B22 . C32 . N55 . Q43

Introduction

The choice of energy policies in Brazil is comparable with global energy standards. The country has made improvements in the electricity usage policies that have motivated universal access to electricity in new regions in the country. An estimat- ed 45% of energy needs in Brazil is supplied by renewable sources (Pao and Fu2013). Since 1990, the total prime energy requirements in Brazil have doubled. There has been an increasing expansion of hydroelectric power in the country that has motivated economic growth (Clottey et al.2018). Demand for transport fuels has also improved the way that the economy grows in that newer methods of connecting regions in the country have been developed. With this, as demand for fuel increased and is still increasing, more income and capital are driven into the economy.

Brazil has a significant amount of operational flexibility that is linked to the presence of large hydropower plants that account for over 75% of the total domestic electricity

generation. There has been an increasing expansion of hydroelectric power in the country, but its potential is limited by the remoteness and sensitivity in the environment in the remain- ing resource. At the moment, there is a 20GW hydropower industry that is built to increase the production of energy and meet the needs of the new industries that are being established in the country (Pao and Fu2013). Elasticity in the source of power in the country is also increasing. For instance, the use of natural gas and wind has also been developed in rural regions (Dinh and Shih-Mo2014). Such power plants have increased the growth of rural areas and provided jobs for most of the people in the affiliated regions. Diversification in the production lines and transmission capacity has been improved by the influx of international investors that have provided a basis for which energy production and usage in the country can be improved.

The discovery of large offshore oil and gas rigs, Brazil has been recognized as one of the world’s advanced oil and gas regions. Petrobras, a national oil company in Brazil, has been granted a central role in the country in regard to strategic regulation of petroleum consumption (Pao and Fu 2013).

With new developments in deep water mining of oil, Brazil is preparing to secure its position as a net oil exporter.

Forecasted estimates show that the country could export up to 1 million barrels per day of oil by the end of 2022. This will be a great push in revenue generation that would later increase Responsible editor: Muhammad Shahbaz

* Marco Mele [email protected]

1 Department of Economics, University of Teramo, Teramo, Italy

/ Published online: 15 August 2019

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the GPD with time. This paper aims to examine the relationship between real per capita GDP and energy consumption in Brazil for the period 1980–2017, using methodologies based on time series econometric approach.

Literature review

Numerous authors have addressed the literature on economic growth and energy consumption (Kraft and Kraft 1978;

Akarea and Long1980; Erol and Yu1987; Masih and Masih 1996; Stern2000; Soytas et al.2001; Chontanawat et al.2006;

Rufael 2006; Costatini and Mattini 2009; Bright and Machame2011; Mehdi and Maamar2012; Mele2019, etc.).

In general, according to Squalli (2007), the causal relationship between energy consumption and economic growth involves the following directions: (a)“Neutrality hypothesis”: when there is no causality between energy consumption and GDP;

(b)“Conservation hypothesis”: when there is unidirectional causality running from GDP to Energy; (c)“Growth hypothesis”: when there is unidirectional causality running from energy to economic growth; (d)“Feedback hypothesis”: if there is, instead, bidirectional causality between energy consumption and economic growth.

In sum, therefore, literature dealing with this topic indicates different results such as bidirectional causality, no causality, or unidirectional causality between the two variables. Depending on policy in a country, causality will differ. A unidirectional causality shows that any energy policies do not affect the economy. Chen et al. (2007) found this kind of causality in Malaysia, India, and Singapore. A bidirectional causality indicates a two-way system whereby both the economy and energy usage depended on the other. This kind of causality was identified by Morimoto and Hope (2004) to exist in Sri Lanka. These results confirm those of Pao and Tsai (2011) as well as Pao and Fu (2013) study, who found a bidirectional model between energy usage and real GDP growth in Brazil.

No causality shows no association exists the two variables.

This kind of causality was found by Chen et al. (2007) to exist in Thailand and China.

Literature studying the link between energy consumption and the economy varies since the distribution of energy resources in the world is varying. Additionally, the economic implication of energy use on the economy also varies since different countries rely on different kinds of energy to drive the economy. Arab countries, for example, have abundant access to fossil fuels, and this situation is not the same in countries such as Brazil. The proportion of access, therefore, varies making the empirical study of the relationship between economic growth and energy usage complex.

Otoo and Drechsel (2018) found that Brazil holds in the 9th position in the production of liquid energy the American conti- nents. In 2017, the country produced over 3.36 million barrels

per day of fossil energy and other liquids. Additionally, in the same year, Brazil was the 8th largest consumer of energy in the world. Forty-six percent of Brazil’s domestic energy usage in 2017 was accounted for by petroleum and other liquids. These energy production and consumption statistics put Brazil as the largest country in the field in South America. With 12.6 billion barrels of the reserved oil in 2018, Brazil is a country that can provide for its energy needs. Over the years, economic shift and implications such as the 2008 global recession have greatly affected the country’s GDP. Between 2008 and 2009, the rate of unemployment in the country increased by 1.264%, which was a great hit to the country’s economy. However, these rates have fluctuated between 2008 and 2018 with the country developing new economic policies to deal with the changes in the needs of consumers and industries in the country.

A study by Costa (2001) found that policies made by gov- ernments regarding energy consumption are more efficient when they are integrated into the needs of industries and consumers at large. In Brazil, energy policies have evolved between 1980 and 2014 (Dinh and Shih-Mo2014). This is attributed to the changes in the comfort of life in consumers and the automation of various processes in industrial processes.

The implications of energy policies in Brazil are also linked to the availability of energy production channels and their ability to affect both rural and urban populations. De Freitas and Kaneko (2011) found that urban and rural communities have different energy needs, and the distribution of energy in both sectors immensely varies.

Model

From the above literature, it is possible to form a model that relates real GDP per capita and energy usage in Brazil (sources in Table1). Using natural logs, the model used in this paper is NEC_i=β0+β1NGDP_i+ui where NEC and NGDP represent the energy usage and real GDP, respectively.

urepresents the error in the above model, and it is assumed to be independent of the predictor variable, which is energy consumption. Furthermore, the sum of the error terms is assumed to be zero and has constant variance. Income elasticity, in the long run, using the above model is given by theβ1and is supposed to be higher than zero since the growth in the economy should increase the rate of energy consumption.

Econometric methodology

The error correction model is used to capture the Granger connection concerning the two variables in the above regression equation. This process is done in three main steps. First, the integration order for both variables in the equation is checked. This information is crucial in cointegration tests

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since they only apply to variables with the same order. After confirming the presence of identical integration order, the Johansen ML technique is employed to assess the cointegration association between the variables in the regression model developed above. Additionally, we use Granger causality test and VECM to study the causal direction of our variables in time series.

The model below shows the error correction method used in this paper:

ΔNEC_t¼γ10þ∑ⁿ_i¼1¹ γ11iΔNEC_t−1þ∑^k_i¼1¹ γ12iΔNGDP_t−1 þδ1ECT_t−1þμ_1t ð1Þ

ΔNGDPt¼γ20þ∑ⁿ²_i¼1γ_21iΔNGDPt−1

þ∑^k_i¼1² γ_22iΔNEC_t−1þδ2ECT_t−1þμ_2t ð2Þ

where ECT_t−1is given by NEC_t−1b0−b1NGDP_t−1.

This equation is derived from the association of cointegration between real output and energy usage in the regression equation.ΔNECthas a maximum lag ofn. On the other hand, the means are uncorrelated error terms that are serial.δ2represents the rapidness of change in the adjustment coefficient that shows the rate at which the energy consumption variable affects the equilibrium relationship regarding economic growth (Dinh and Shih-Mo 2014). The model above can measure the short-run and long-run causality

relationship between the two variables since both of these variables are presented together with their lags. The econometric association between these two variables is present whenH0:γ12i=δ1= 0 is denied.

Figure1shows the historical trends of real per capita GDP per capita, energy consumption for Brazil in a log scale, and Table1describes the list of our variables.

As we can see in Table2, mean presents a positive value for all variables; 10-Trim values are near the mean; the interquar- tile range shows the absence of outliers.

The mean energy usage for Brazil between 1980 and 2017 was 70,078 with a standard deviation of 0.17788. The average real GDP per capita for the country was 91,152 with a standard deviation of 0.14769. The average growth rate for energy consumption for the country in 1980 and 2017 was 9.73. On the other hand, the average growth in the real GDP between the same years was 6.50.

The correlation analysis shows that, in our dataset, the variables are strongly correlated: corr (NGDP, NEC) = 0.9616.

These results are confirmed by economic theory: since the increases in real GDP per capita today are correlated with future increases in energy consumption per capita and vice versa.

The Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test results found atstatistic of 1.91 with asymptotic critical values of 0.74, 0.46, and 0.35 at 1%, 5%, and 10% levels of significance. This shows a lack of stationarity in the data used, but only stationary in first differences.

Fig. 1 Real per capita GDP and energy consumption for Brazil. Sources: TED and IEA data Table 1 List of the variables

Variable Explanation Source

NGDP Per capita GDP in 1990 US $, converted at Geary–Khamis PPPs Total Economy Database (TED) NEC Per capita energy consumption, kg of oil equivalent International Energy Agency (IEA)

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Empirical results

The values obtained in first differences and levels through KPSS test may have been affected by shocks arising from changes in economic policies, as currency crises or exogenous recessive cycles worldwide character. Therefore, to mitigate the mislead- ing results, we performed the ZA and CMR tests, in order to verify the presence of structural breaks (Tables3,4, and5).

From Table4, we can note that the break detected by the CMR test roughly corresponds to the timing of the imple- mentation of austerity policies in Brazil after the Mexican crisis of 1982 for NGDP, and the introduction of a new currency, the Real, anchored to the dollar, for PCEC.

Despite the structural interruption, we are unable to reject the null hypothesis on the unit root in these series; however, if we perform the test at the first differences, our series become stationary. Since the results for CMR test also confirm previous findings (Table 5) we can conclude again that GDP and energy consumption are I(1) processes.

The results just obtained suggest the use of the Johansen and Juselius approach (Table6). These cointegration tests, which are applied in this paper, are useful for finding the long-term relationship between real GDP per capita (NGDP) and energy consumption (NEC). The selection of the delay order was cho- sen based on the final forecast error (FPE), the Akaike information criterion (AIC), Schwarz’s Bayesian information criterion (SBIC), and Hannan and Quinn information criterion.

As we can see from the table above concerning the trace test, the null hypothesis of non-cointegration is rejected at 5%

level of significance and this is so for every equation considered. However, if we consider the hypothesis in the tableH0: r0= 1, null hypothesis is accepted at the 5% significance level.

These results show that the two time series of NEC and NGGP present a cointegration equation; in particular, we can

highlight the presence of a long-term relationship between real per capita GDP and per capita energy consumption for Brazil.

Such turnout, in turn, emphasizes the existence of the causality of Granger, without indicating the direction of causality.

We can see a similar result in Table7.

Cointegration tests based on the VECM with 2 lag (Table8) show the presence of a connection association between growth in the real output and energy usage in Brazil. In the short run, a unidirectional connection is present in the two variables. This means that through a feedback system, change in variable affects the outcomes in the economy or energy sector in Brazil. However, in the long run, a two-way connection exists amid the two variables regarding dynamics in Brazil. Additionally, a strong Granger relationship exists between the consumption of energy and the economy in Brazil.

From the above results, the econometric relationship between real output and energy usage in Brazil is easier since the causality relationship can be reviewed in several factors that may affect both variables. Various constraints in the economy would have different effects on the way that the country’s energy usage would be. Such outcomes will be analyzed in the

“Discussion”section using these results.

Discussion

From the results, several policy implications can be linked to the association between energy use and the economy in Brazil.

Brazil is a developing country that has the potential for growth in many sectors in the economy. Specifically, the energy sector in the company has realized steady growth from 1980 to 2017.

Within this period, the country has had numerous changes to energy policies, some of which address the way that energy is consumed in the country. Therefore, to comprehend the association between energy consumption and GDP in Brazil, it is critical to review policy changes that have influenced the kind Table 2 Exploratory data

analysis Variable Mean Median SD Skewness Kurtosis 10-

Trim

IQR

NGDP 9.1152 9.0681 0.14769 0.51208 1.0141 9.0945 0.25482

NEC 7.0078 6.9764 0.17788 0.67373 0.68882 6.9915 0.27167

Table 3 Results for unit root tests with structural breaks

Variable a b

T k tmin T k tmin

NGDP 1981 1 −0.614 1983 1 −1.085

NEC 1992 1 −2.975 1987 1 −2.106

ΔNGDP 1982 1 −4.105** 1984 1 −4.258***

ΔNEC 2014 1 −6.258*** 2015 1 −5.95***

aBreak in intercept and^bbreak in trend.Tis the break date endogenously selected.Tminis the minimumtstatistic.kdenotes the lag length

Table 4 Results for additive outlier unit root tests (single structural break)

Variable Optimal break point k t 5% crit. value

NGDP 1982 1 −3.125 −3.50

NEC 1992 1 −4.050 −3.50

ΔNGDP 1983 0 −5.025* −3.50

ΔNEC 1996 0 −6.345** −3.50

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of causality that exists between these two variables. Energy is, therefore, one of the most crucial growth engines in an economy. The long-term and short-term relationship between the two variables in this study have significant implications in the outcomes regarding economic decisions in a country. For efficient growth, relevant laws and policies are needed to regulate the nature of the causality relationship between the two variables. It is required that each of the variables depends on each other, and any shock in the system provided positive growth in the economy (Ma2007). However, dependence on high energy use has several negative implications in a country. For instance, the proliferation of industries increases the amount of carbon diox- ide emissions. This scenario presents several impacts to the environment in Brazil and the kind of investment that is needed to maintain a healthy environment.

From a time series perspective, the growth in energy consumption in Brazil has been affected by several factors that are linked to the country’s social, political, and economic status (Leite2009). Taking these factors as a multiple regression model can give more insight into their effects on the economy of Brazil. Factors that affect energy consumption are correlated and have a general impact on the way the economy reacts to changes in socio-economic landscapes. Existing patterns in energy use in Brazil depend on the complex association between these factors. These factors include land ecology, pop- ulation density, land use pattern, income levels in an economy, exporting regions, and closeness to energy sources (Hutzler et al.1998). Depending on the kind of needs in an economy, the energy consumption rates vary.

Based on the results from this study, it is true that energy use and real GDP are correlated and learning the basics of this correlation builds a critical analysis of the time series data of these variables between 1980 and 2016. The role of fuel consumption in maintaining the economy in Brazil is, therefore,

critical to this study (Borgstein and Lamberts2014). Brazil is a potential oil producer, and it is projected that the country will have a viable future due to the discovery of more oil rigs in various regions. Industries and households are the most energy-dependent entities in Brazil. Domestic energy consumption in Brazil has a steady increasing trend between 1980 and 2016 (Otoo and Drechsel2018).

Reducing the rate of energy consumption is a necessity in Brazil since it controls the emissions and effects that energy- using entities in the country have on the environment. It has been found that there has been a constant depletion of fossil energy in the world, and hence, policies to manage energy consumption in countries such as Brazil are a viable solution.

The country is now focused on renewable sources to regulate the dependence on fossil energy (De Freitas and Kaneko 2011). In the time series data of energy consumption and real GDP in Brazil, a Granger causality exists between the two variables. This shows that the kind of energy consumption patterns in Brazil can be used to predict the future of the economy (Costa2001). Reviewing the future implications of energy consumption on the economy is useful in predicting the nature of the time series.

Energy consumption has several implications on the environment, and controlling these effects is an indicator of a strong administration that improves the lives of individuals. A sustainable environment that is free from emissions and pollutants encourages growth in the economy (Carvalho et al. 2010).

From this argument, the role of policy-making regarding energy consumption to the economy can be seen. For instance, Brazil’s energy policies are stipulated in the Ten-Year Expansion Plans that are upgraded and changed annually based on the state of the nation. The National Energy Saving Plan that was developed in 2007 had many implications on the kind of effect that energy usage in Brazil had on the economy (Bhattacharyya 2011). Fast forward to 2018, energy policies in the country Table 5 Results for additive outlier unit root tests (two structural break)

Variable Optimal break point k t 5% crit. value

NGDP 1983,2014 1 −5.125 −5.50

NEC 1996,2013 1 −6.050 −5.50

ΔNGDP 1982,2015 0 −5.625* −5.50

ΔNEC 1995,2014 0 −7.345** −5.50

Table 6 Johansen and Juselius procedure. Results for cointegration tests

J-J procedure

Rank = 0 Trace statistic 5.6071 (5% critical value 16.46) SBIC−7.4190

Log-likelihood 273.133 HQIC−7.6582

Max.-eigenvalue statistic 5.3511 (5% critical value 7.14) AIC−7.8524 Rank = 1 Trace statistic 0.50839 (5% critical value 6.15) SBIC−8.9421

Log-likelihood 274.315 HQIC−9.0945

Max.-eigenvalue statistic 9.1203 (5% critical value 15.67) AIC−10.005 Table 7 Results for cointegration tests NEC-NGDP

Engle and Granger procedure

N t-stat 1% critical value 5% critical value 10% critical value

37 −1.825* −2.142 −1.920 −1.505

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are now focused on improving the use of renewable energy sources to reduce the effect of pollution in the environment.

The Granger causality between energy use and the economy is strong and bidirectional. This shows that both variables are jointly correlated and affected at the same time (Bosselman2006). Between 1980 and 2017, the causality has played a significant role in the determinations of major strategic decisions to improve the economy in Brazil. This time series approach is therefore important in understanding the implications of increase or decrease of energy consumption on the economy and how to manage the attributes of different sectors in the economy. Energy efficiency in Brazil has had a great impact on economic outcomes in Brazil.

This relationship is explained by the Granger causality that is analyzed between the two variables in this study. Therefore, the impact of energy efficiency in Brazil has been positive based on the way that the economy has grown between 1980 and 2016. With this information, it is correct to state the increase in consumption of energy in Brazil has improved the economy. This scale effect describes the reason behind the proliferation of technological advances in energy use and how much impact they have had on Brazil and its economy at large.

The methods of energy production in Brazil have also changed between 1980 and 2016. From the results in the study, real GDP has steadily increased between this period. This is an indicator of growth in income per capita, which has a major effect on energy consumption in Brazil. Understanding this relationship, therefore, needs a review of techniques that improve energy consumption in Brazil. In the last 20 years, Brazil has invested in the management of energy sources and ways to strengthen the implications of the economy in growth of energy use (Al-Mulali et al.2016). At the same time, techniques of energy production determine the profitability in each unit of energy consumed in Brazil. Hydroelectric power is cheaper for individuals in short, but renewable sources such as Solar are more preferred in the long run. This association is critical in the understanding of purchase decisions of energy source between 1980 and 2017. The choice of energy source preferred by individuals often affects the economic outcomes in any country.

Such preferences have shifted since 2008 due to the effects of the global financial crisis that lead to the plummeting of living standards in many countries around the world.

As the country constantly seeks growth in its economy, Brazil needs to invest more in improving efficacy in energy use together with appliances and equipment. Energy policies regulating efficiency in home appliances and equipment en- sure that households are well positioned in the growth patterns

in Brazil’s economy (Almeida and Rosenfeld 2012).

Additionally, reducing the loss of energy in transmission and distribution channels also improves the effect that energy consumption has on the economy. Tariffs to control energy consumption patterns are a viable solution to improve fuel and energy efficiency in Brazil.

Comparing the time series analysis data of Brazil and world statistics gives more insight into the econometric relationship between energy use and the economy. Based on the results of this study, there exists a causality link between the two variables. This result is, however, not steady with studies done in countries such as Singapore (Costa2001). Such countries have been found to have no relationship between energy consumption and the economy. With this information, the econometric relationship between the use of energy and the economy in Brazil can be reviewed from different perspectives based on energy and economy dynamics. For instance, there exists a variance between energy consumption patterns in many countries around the world. This is attributed to the fact that there exist different economic needs in the government based on the structures in each country. Furthermore, to understand the econometric relationship between these variables, researchers have employed different techniques of study. This has led to the divergence of results hence changing perspectives on the link.

Conclusion and recommendations

Energy is a crucial part of any economy and holds a central position in enhancing social development in the world. The econometric association between energy consumption and Brazil is affected by numerous factors. These factors include preferences in energy choices in the economy, energy production techniques, the scale of energy use, and the investment made by Brazil on regulating energy. Energy policies are one of the most important regulatory factors in the management of the effect that energy has on the economy (Ma2007). Based on the results of this study, a bidirectional Granger relationship exists between real GDP and energy use in Brazil.

Furthermore, a positive correlation exists between the two variables, which indicate that an increase in energy usage has a subsequent increase in real GDP in Brazil.

Based on the implications that energy consumption has on the economy, it is true to say that proper management of energy use in an economy improves the state of the nation regarding its position in markets around the world. Between 1980 and 2016, there have been numerous changes in Table 8 Results for short- and

long-run causality tests Lags Log- likelihood

SBIC Causality in the long run Causality in the short run

2 173.2625 −8.4513 NEC↔NGDP NEC→NGDP

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structures, needs, and factors affecting the causality association between energy usage and the economy in Brazil (Otoo and Drechsel2018). Therefore, a review of each specific ele- ment and understanding the scale of its effects is critical in the understanding of the relationship in the subject.

It is recommended that Brazil adopts a dual strategy that will improve both the economy and energy efficiency.

Balancing the growth of both these variables is an indicator of sustainable growth that enhances the country’s development goals. Investment in energy infrastructure is also a viable strategy to increase energy efficiency (Geller2012). Policies to promote energy conservation should also be created to en- hance the management of pollution in the country. Such policies will reduce energy wastage and generally increase profitability in each unit of energy consumed in a household or industry in Brazil. Investment in energy policies will, therefore, increase energy efficacy and real GDP.

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