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Energy consumption and economic growth: A panel cointegration analysis for developing countries
... Costantini and Martini (2010), Ozturk and Acaravci (2010) and Omay et al. (2014) identified variation in data series, methodology and sample location as the possible reason for the disagreement in the literature. However, Ighodaro (2010), Chen (2010), Adhikari and Chen (2012) and Omay et al. (2014) found that energy consumption positively expedites economic growth. While incorporating population, Shaari et al. (2013) concluded that population triggers energy consumption while energy consumption accelerates economic growth. ...
... To the best of our knowledge, empirical studies that closely relate to this scientific enquiry, especially for the West African sub-region, are scarce. Most of the similar studies either beamed searchlight on the link between output growth energy use (Mallick, 2010;Adhikari and Chen 2012;Omay et al. 2014;Mesagan et al. 2021a) or analysed the nexus between economic growth and carbon emissions (See Omojolaibi 2010; Boopen and Vinesh 2011;Tang and Tan 2015;Mesagan 2015). Yao et al. (2015) and some others like Mesagan and Nwachukwu (2018), Pata (2018), and Charfeddine and Kahia (2019) identified financial development, urbanization and trade as the medium for energy consumption-led pollution. ...
... Thus, as industrial and domestic pollution increases, it has implications for economic growth as described in the EKC model. Therefore, omitting it as most of the previous studies (Like Mallick 2008;Ighodaro 2010;Chien, 2010;Lau et al. 2011;Adhikari and Chen 2012;Boopen and Vinesh 2011;Charfeddine and Kahia 2019) have done can make the information provided in the study incomplete. However, this study will not only analyse the effect of CO 2 emissions on growth but will also examine the causal relationship energy use, pollution and growth to ascertain the direction of causality among them for West Africa. ...
We adopt the FMOLS and Granger causality technique to analyse the effect of energy use and carbon emissions on output growth in selected West African economies, which includes Nigeria, Gambia and Ghana, from 1970 to 2019. Findings confirm that energy use enhances growth in the three selected West African economies. But in terms of significance, energy consumption is significant in Nigeria and Gambia at a 1% level of significance while it is insignificant for the Gambia. CO2 emission positively and significantly propels economic growth for the three selected West African economies. For Nigeria, causality evidence shows no direct influence among the variables. For Ghana, we find a bi-causal association between output growth and carbon emissions and a unidirectional causality from pollution to energy consumption. For Gambia, economic growth causes CO2 emissions. We recommend that the West African government reinforce their stand on a sustainable growth path through energy conservation.
... Moreover, low usage of local resources like coal and hydrological power in the production of energy leads to energy shortages and hikes in the energy prices [2,6]. Third, most studies concluded that the usage of energy is a cause of environmental degradation [2,14,15], while this study contributes to the literature by investigating the impact of climate change on energy inflation. Finally, this study utilized the vector auto-regressive (VAR) model to investigate the short-run and long-run effects of climate change, the exchange rate, and a twin deficit on energy inflation. ...
... Increasing the energy demand forced us to import more and more energy to fulfill the requirements. If the country failed to import energy, there would be dire consequences for the economy because energy consumption has a direct link with the economic development of a country [15,21]. Moreover, energy consumption is also directly associated with industrialization, urbanization, financial growth [22], technological advancement, and social development [17]. ...
The motivation behind the study is continuous fluctuations in energy prices in Pakistan, so this study aims to investigate the role of a twin deficit, urbanization, climate change, energy production from oil and gas, and the exchange rate in energy inflation. This study utilized oil prices and electricity prices to capture energy inflation using time series data from 1972 to 2021, from World Development Indicators (WDI) and the Census of Electricity Establishment (CEE). This study utilized the vector auto-regressive (VAR) model to investigate the short-run and long-run estimates. This study found that the twin deficit and the exchange rate have a significant and positive association with energy inflation. However, the size impact of the twin deficit is greater on oil prices as compared to electricity prices. Furthermore, urbanization, climate change, and energy production from oil and gas have a positive and significant long-run association with electricity prices. Moreover, the results of the variance decomposition test indicate that the relative contribution of the budget deficit in electricity prices (Model 1) is greater than other modeled variables, while the relative contribution of the budget deficit and climate change is greater in oil prices (Model 2), as compared to other exogenous variables. This study helps policymakers to devise policies to control energy inflation, which affects the well-being of society.
... This analysis includes LLC test that supposes that there is a regular unit root process across the cross-sections. Panel unit root tests such as IPS, ADF and PP test assume that there are individual unit root processes across the cross-sections (Adhikari, Chen, 2012). The panel cointergation test is often used to identify the existence of the long-run equilibrium relationship between two or more variables. ...
... The panel cointegration test enables for cross-sectional interdependence with both different individual effects and deterministic trends to be determined as: lnYit = αit δit βilnEit εit εit=ρitεit-1 + uit (1) where i = 1,……N reflects the panel member, t = 1,……T refers to the time period, Y reflects the GDP, TET reflects the total environmental taxes and βi reflects the slope coefficient. The parameters αit and δi let for possibility of country-specific effects and deterministic trend effects, where εit manifests the evaluated residual deviations from the long-run nexus (Adhikari, Chen, 2012). ...
The issue of security and safety i s a fundamental condition for stable economic trends. Military expenditure can be a very powerful tool for a rapid economic growth. The paper examines the long-run relationship between military expenditure and economic growth in the selected Balkan countries, such as Albania, Bosnia and Herzegovina, Croatia, Montenegro, North Macedonia, Serbia and Slovenia for the period 2004-2018. The analysis implies a panel unit root test, a panel cointegration test, as well as a panel Granger causality test. The results have identified a long-run relationship between military expenditure and economic growth in the Balkan countries based on panel data analysis. Also, empirical findings have confirmed that shock experience in one of the countries’ military expenditure and economic growth have effect on other countries. Finally, the results have determined unidirectional causality from military expenditure to economic growth in these countries and not vice versa.
... Besides they found that demand shocks and risk shocks either have zero asymmetries or are weak; and in most cases, risk shocks have the weakest impact on inflation and their effect fades quickly. Adhikari and Chen (2012) conducted a study to examine the longterm relationship between energy consumption and economic growth in 80 developing countries from 1990 to 2009. They employed the panel unit root test, panel cointegration test, and panel dynamic ordinary least squares (DOLS) methods. ...
In 2001, Jim O’Neil coined the term “BRIC” to refer to the economies of Brazil, Russia, India and China. In 2011, South Africa joined the group, and it was updated to “BRICS”. These countries have a significant impact on the world economy, and there are numerous studies examining their macroeconomic structures. This study focuses on the relationship between economic growth, oil revenues, and inflation levels in BRICS countries from 2000 to 2021 and uses panel cointegration analysis. Many studies showed a relationship between these variables in different countries and unions. This study aims to determine if these relationships hold for BRICS countries. The results suggest a cointegration relation and a causality relation between economic growth, inflation, and oil revenues in BRICS countries. This finding demonstrates the impact of energy, specifically oil revenues, on economic growth. However, other macro indicators also affect economic growth, as suggested by existing literature. Therefore, future studies could improve on this research by including additional social and economic variables to evaluate the impact of oil revenues on economic growth from multiple perspectives.
... Considering that both factors are strong contributors to a nation's GDP, the relationship between energy consumption and economic growth can be adequately interpreted (Adhikari and Chen, 2012;Rezitis and Ahammad, 2015b;Tang and Shahbaz, 2013). ...
The purpose of this paper is to empirically and economically investigate the causal relationship between economic growth and energy consumption in five countries with high consumption during the period of 1968-2016. These countries are China, India, Japan, the United States, and Saudi Arabia. Using the cointegration relationship between the variables procedure and the Granger causality test. This period witnessed various changes in the economy, consumption, and production of these countries. The causality results for the countries show that there is a unidirectional, and bidirectional Granger causality between the variables. Therefore, the energy conservation policy should be designed with caution, as energy is an engine for gross domestic product growth.
... where i = 1,…N reflects the panel member, t = 1,…T refers to the time period, Y reflects the GDP, TET reflects the total environmental taxes and βi reflects the slope coefficient. The parameters αit and δi allow for possibility of country-specific effects and deterministic trend effects, where εit manifests the evaluated residual deviations from the long-run relation (Adhikari, Chen, 2012). ...
This paper examines the relationship between total environmental taxes and economic growth for twenty-eight EU countries from 1994 to 2018. The aim of this research is to evaluate the long-run relationship between these variables based on panel data analysis. The analysis includes panel unit root test, panel cointegration test, panel ordinary least squares, panel dynamic ordinary least squares, as well as, fully modified ordinary least squares models. The results reveal long-run cointegrated relationship between total environmental taxes and economic growth in selected countries. Likewise, there is a significant relation running from total environmental taxes to economic growth measured by gross domestic product rate. Empirical findings confirm that revenue of environmental taxes have a positive and statistically significant effect on economic growth measured by gross domestic product rate in the long-run.
... Developing countries are open and dynamic nations that face multifaceted challenges, e.g., energy insecurity, poor economic growth, low standards of living, lack of investment in infrastructure and technologies, as well as low institutional quality [25]. Recently, more than 170 developing nations have been bestowed with natural resources, but low levels of economic growth and fundamentals of innovation have inaugurated ineffective utilization of energy [26,27]. Moreover, these developing economies together account for approximately 66% of the population, 57.2% of primary energy consumption, and 61.8% of carbon emissions, but only 36.5% of global growth, reflecting their high level of energy and carbon intensity as well as extensive economic development. ...
... There have been four major findings identified so far. (1) The causality between electricity consumption and economic activity is unidirectional (Akomolafe & Danladi, 2014;Pathan & Abasi, 2014;Shaari et al., 2012;Adhikari and Chen, 2013;Kakar & Khilji, 2011;Orthewere and Henry, 2011;Odhiambo, 2010;Akinlo, 2009;Narayan & Singh, 2007;Altinay and Karagoal, 2005;Wolde-Rufael, 2006), (2) unidirectional causality from economic activity to electricity consumption (Hossain, 2013;Adhikari and Chen., 2012;Akinwale et al., 2013;Shaari et al., 2012;Ahmad et al., 2012;Kwakwa, 2012;Noor & Siddiqi, 2010;Hye & Riaz, 2008;Binh, 2011;Yoo & Kim, 2006;Kraft & kraft, 1978); (3) Bidirectional causality between electricity consumption and economic activity (Akinlo, 2009;Hye & Riaz, 2008;Kaplan et al., 2011;Aktas & Yilmaz, 2008;Chen et al., 2007), and (4) no causality between electricity consumption and economic activity (Ghaderi et al., 2006;Zou & Chau, 2006;Akinlo, 2009). ...
Based on what we know today, there is a strong linkage between solar activity and the energy sector. In this work, we study the linkage between extreme solar events and the US energy sector, utilizing a sectoral supply chain dataset that spans the period 1998–2014. To do so, we propose a novel methodological approach by linking all the sectors of the economy’s supply chain through a network-theoretic production-based framework. We estimate the network system using a global vector autoregressive model that incorporates dominant entities. Additionally, to capture the indirect spillover impact of extreme solar events on the rest of the sectors in the US economy, we develop, for the first time in the literature, the indirect global impulse response functions. We find that solar events affect directly the energy sector and, indirectly, most of the other sectors of the US economy. More precisely, solar phenomena indirectly provoke positive and significant responses in manufacturing, transportation, information and communication, finance and insurance, real estate, and business activities, through the energy sector. Conversely, agriculture, forestry, fishing, and mining sectors exhibit negative and significant responses. Construction, accommodation and food service activities, and wholesale and retail trade sectors do not show any significant response. These results give credence to the impact of solar events on the US sectoral economy, directly and indirectly, through the proposed IGIRFs.
... In the same way, Korkmaz and Yilgor (2011) conducted a cointegration analysis by applying CADF and CIPS tests with annual data for the period of 1980-2004 for 26 countries and achieved a result in the same direction as previous studies. Adhikari and Chen (2012) who achieved a positive relationship result, analysed the relationship with long-term cointegration analysis for a total of 80 countries divided into three groups: upper middle income, low middle income, and low-income countries. Streimikiene and Kasperowicz (2016) conducted cointegration analysis, including fixed capital investments and total employment data, in addition to the relevant variables, to examine the relationship for 18 European Union member states from 1995 to 2012. ...
In the study, panel data analysis was conducted on 32 OECD countries covering the period 1990-2018. To analyse the effect of energy consumption on economic growth, first, a cross-section dependence test of the variables was carried out, then CADF Test, which is the most suitable unit root test based on the obtained results results, was applied. According to the findings of the Hausman, autocorrelation, and heteroscedasticity tests, it has been decided to use the Driscoll-Kraay test for the model’s forecast. The forecast results demonstrate that energy consumption positively affects economic growth. Westerlund ECM Panel Cointegration Test was conducted to determine the long-term relationship, and it concluded that the variables acted together in the long term. Emirmahmutoglu & Kose and Dumitrescu & Hurlin tests were used to determine the direction of the relationship between energy consumption and growth. Through the results of both tests, a maximum number of countries emerged respectively in the null hypothesis with no causality relationship and then in the growth hypothesis explaining the causality relationship from energy to growth. Along with the panel fisher and panel Z_NT test results of both causality tests, a causality relationship has been detected from energy to growth.
... Referring to Figures 1 and 2, it could be seen that economic growth has a stable trend in the range of 5%, while energy consumption growth showed a declining trend. However, previous empirical study by Lolos (2002), Mahadevan (2007), Pradhan (2010), Apergis and Payne (2010), Rezki (2011), Adhikari and Chen (2013), Nnaji et al., (2013), Susanto (2013) Ishida (2013), Ouedraogo (2013), Purbaningrum (2014), Iyke (2014), Fariz (2015), Nazer and Handra (2016), Zuldarepa (2017), Akandy (2017), Fauzi (2017), Ula and Affandi (2019), and Setiawan et al. (2019) showed that energy consumption has a positive effect on economic growth. ...
The economic growth in Indonesia showed a stable trend while the growth in energy consumption showed a declining trend. However, previous studies had revealed the existence of positive and significant relationship between energy consumption and economic growth. This study aims to analyse the effect of oil, gas, and biomass fuel consumption, road infrastructure, life expectancy, and average length of education on economic growth in Indonesia during the year of 1990-2019. This study used quantitative approach with linear regression as data analysis method. The data used are time series data from the period of 1990-2019. The result of this study showed that oil, gas, and biomass fuel consumption, as well as average length of education have a positive and significant effect, while road infrastructure and life expectancy have no effect on economic growth in Indonesia for the year of 1990-2019. This study recommends: 1) energy reserves should be improved by increasing the number of energy sources and developing more infrastructure in order to support and boost the supply of energy, 2) quality of educations should be upgraded by giving out scholarships as well as improving the educators and physical infrastructure.
... This concept consists of energy and raw material combinations. This measurement concept data can also be evaluated as a technological development measurement (Yıldırım, 2019 Adhikari and Chen (2012) considered 80 developing countries based on causality relationship between the GDP and the EC via DOLS method. It was resulted that there is a causality from GDP to EC in low-income countries. ...
... The test is for dynamic heterogeneous panels and reports the mean of individual unit root statistics, proposing standardized t statistics and following averaged-augmented Dickey-Fuller statistics [49]. This method is widely used in empirical literature to model the energy-GDP nexus as it allows to uncover the directions of causality when using panel data [51][52][53]. ...
The purpose of this study is to shed light on the nexus between electricity supply and economic growth in South Asian countries during 1990-2018. The study employs Pedroni's panel cointegration test as well as Dumitrescu and Hurlin's (DH) causality test for panel data. The empirical results confirm a long-term relationship between electricity supply and economic growth. We fail to reject the non-causal relationship between electricity supply and economic growth for the panel, thereby affirming the neutrality hypothesis. Single country causality analysis reveals the growth hypothesis in the case of Pakistan. These results have a number of policy implications. For example, governments can introduce measures to improve energy efficiency in Bangladesh, India and Sri Lanka without fear of harming economic growth. The results for Pakistan may also imply that fostering green energy generation would lead to a positive effect on economic growth via improved electricity production. The government may use various policy tools to stimulate adoption of renewable energy, such as fiscal incentives, low interest loans, or grants for rural populations to speed up the green energy transformation.
... Among which, electricity is the lifeline and the backbone in modern economic development [8,16]. Most research focuses on the energy consumption-economic growth nexus [17][18][19], where the causal relationship between energy consumption and economic growth is still controversial [20][21][22]. However, there is scarce literature, compared with electricity consumption, focusing on the important role that ESQ plays in economic growth [9], and most of the existing studies quantify the reliability cost on different types of consumers [15,23] rather than on the macro economy. ...
Electricity supply quality (ESQ) is critical for healthy economic production, and regional differences in ESQ can widen economic development gaps. To contribute to a more equitable regional development, this study first develops a Gini index of ESQ distribution to measure the inequality among different cities. Then, an econometric model based on the Cobb–Douglas production function is established to quantify the effects of ESQ on regional economy. Finally, we estimate the impacts of ESQ improvement on reducing the economic inequality. The main results show that: (1) Substantial differences exist among the regional ESQ, and the national GDP-based ESQ Gini index was 0.720 in 2018. (2) A GDP-based Lorenz curve has a higher Gini coefficient than the population-based one does, while inequalities in cites are greater than those in rural areas. (3) The ESQ has significant impacts on the regional economic output, and a 1% reduction in the ESQ will, on average, reduce the city-level output by 0.142%. (4) ESQ improvement can significantly narrow the economic gap by up to 24.9%, that is, the ESQ Gini index of GDP distribution will decrease from 0.329 to 0.247 according to our scenario designs.
... This technique is applied to confirm whether variables have a long-run liaison between two or more variables. The panel co-integration of Pedroni [65,66] has two types of test; firstly, within dimension established on the (panel cointegration statistics) has four test statistics: namely, panel v-statistics, panel rho-statistics, panel PP-statistics and panel ADFstatistics. Secondly, the cluster test centered on between breadth (group means panel co-integration data) established on three tests, specifically, Group rho-statistic, Group PP-statistics and Group ADFstatistics. ...
Internationally, the importance of clean energy is greatly appreciated in the context of sustainable development and to protect the atmosphere. Therefore, the objective of this article is to determine the effect of natural gas, renewable energy and nuclear energy consumption on economic growth and carbon dioxide emissions in the ten highest CO2 emitting countries within a multivariate context for the duration of 1990-2014. The panel co-integration test, panel fully modified ordinary least squares and panel heterogonous Dumitrescu and Hurlin causality assessment are used to analyze the estimation of long-run elasticity along with the course of causality among the variables. The panel co-integration test confirms the existence of a long-run equilibrium correlation among the variables. The findings of the long run elasticity and causality test reveal that natural gas does not contribute to economic growth and CO2 reduction like nuclear energy and renewable energy. However, except for natural gas, the expansion and improvement of renewable energy and nuclear energy are vital to avoid global warming and climate change as well as to promote economic growth.
... There are a wide range of literatures discussing about the role of the energy demand on economic growth. Most of the studies support the positive energy-growth association (such as Rahman et al., 2015;Kasperowicz, 2014;Yildrim et al., 2014;Adhikari and Chen, 2012;Narayan and Smyth, 2008;Lee, 2005;Soytas and Sari, 2003;Imran and Siddiqui, 2010;Masih and Masih, 1996). The following section provide several discussions about the literatures of the relationship between energy consumption and economic growth. ...
... Hence, energy is as important as other factors for economic growth such as labor and capital. Several studies suggested that energy consumption plays an important role in determining economic growth [1][2][3]. Cassim et al. (2004) stated that energy is used for economic development as it generates economic activities [4]. Ozturk et al. (2010) found that in upper and lower-middle-income countries, energy consumption is the determinant of economic growth [5]. ...
The issue of energy has been debated among policymakers and economists. Energy plays an important role in generating economic activities. On the other hand, it can have deleterious impacts on the environment as more carbon dioxide (CO2) emissions will be released. Most previous studies focused on total energy rather than types of energy such as oil and gas in investigating the effects of energy consumption on CO2 emissions. Therefore, this study investigates the effects of oil and gas consumption rather than total energy consumption on CO2 emissions in 20 Organization of Islamic Cooperation (OIC) countries. The dynamic heterogeneous panel (panel autoregressive distributed lag model – panel ARDL) approach namely pooled mean group (PMG), mean group (MG), and dynamic fixed effect (DFE) were employed. The main results reveal that in the long run, overall national output contributes to higher environmental degradation. However, in the short run, overall national output does not affect CO2 emissions. The results also suggest that the population can reduce CO2 emissions in the short run but leaves no effect in the long run. Besides, gas consumption and oil consumption can have deleterious effects on the environment. The effect of oil consumption is greater than the effect of gas consumption on the environment. Therefore, it is important to consume more renewable energy such as solar, biodiesel, and hydro to replace non-renewable energy, particularly oil, in a bid to conserve the environment.
... The relationship between energy consumption and economic growth analyzed by panel data method in 80 developing countries in the period of 1990-2009, and stated that there was a long term positive relationship between the variables [7]. ...
Energy plays an important role in the economic growth, social development and individuals’ prosperity and comfort of countries. The effect of energy consumption on economic growth depends on the economic structure of the country. In this study, per capita electricity consumption (kwh) and Gross Domestic Product ($) per capita for the period covering 1991-2014 for six countries in Central Asia (Azerbaijan, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan) panel data analysis was used to investigate the relationship between the series. According to the results, the existence of the cointegration relationship among the variables discussed in the examined countries was determined.
... Considering that both factors are strong contributors to a nation's GDP, the relationship between energy consumption and economic growth can be adequately interpreted (Adhikari and Chen, 2012;Rezitis and Ahammad, 2015b;Tang and Shahbaz, 2013). ...
The purpose of this paper is to empirically and economically investigate the causal relationship between economic growth and energy consumption in five countries with high consumption during the period of 1968-2016. These countries are China, India, Japan, the United States, and Saudi Arabia. Using the cointegration relationship between the variables procedure and the Granger causality test. This period witnessed various changes in the economy, consumption, and production of these countries. The causality results for the countries show that there is a unidirectional, and bidirectional Granger causality between the variables. Therefore, the energy conservation policy should be designed with caution, as energy is an engine for GDP growth.Keywords: energy consumption, economic growth, Granger causalityJEL Classifications: C20; Q43; C32DOI: https://doi.org/10.32479/ijeep.7657
... According to the findings, a causality relationship between economic growth to energy consumption in the short term and causality relationship between energy consumption to economic growth in the long term was identified. Adhikari and Chen (2013) analyzed 80 countries for the period from1990 to 2009. From the findings, the causality relationship from energy consumption to economic growth in the upper-middle income countries and low-middle income countries and the causality relationship from economic growth to energy consumption in low income countries was proven. ...
This study analyzes the relationship of causality between energy consumption, trade openness and economic growth for 24 OECD countries. In the study undertaken during 1971 to 2014, the cross section dependency and the homogeneity of slope coefficients were investigated. After determining the heterogeneity of the slope coefficients under the cross section dependency of the Konya (2006) causality test, it was analyzed against four different stages. i) The panel causality relationship between economic growth and energy consumption. ii) The panel causality relationship between economic growth and trade openness. iii) The panel causality relationship between energy consumption and outward openness. iv) According to the results of panel causality analysis between energy consumption and trade openness to economic growth, it was found that unidirectional causality relationship between energy consumption and trade openness to economic growth in Canada, Chile, Iceland, Spain and Sweden.
... Therefore, we cannot apply the conventional co-integration test in the presence of CD. According to Pedroni's Residual-Based Panel Cointegration Tests (1999Kao, 1999;Kök et al., 2010;Granger, 1969;Engle and Granger, 1987;Johansen, 1991;Philips and Ouliaris, 1990;Lee, 2005;Adhikari & Chen, 2012;Jebli & Youssef, 2015) have mentioned cases like this, the research should apply Error Correction Model (ECM) like Driscoll-Kraay standard errors estimations in pooled OLS model. Driscoll and Kraay (1998) standard errors for coefficients estimated by pooled OLS/WLS or fixed-effects (within) regression. ...
... Therefore, we cannot apply the conventional co-integration test in the presence of CD. According to Pedroni's Residual-Based Panel Co-integration Tests (1999,2004), Kao (1999), Kök et al., (2010), Granger (1969), Engle and Granger (1987), Johansen (1991), Philips and Ouliaris (1990), Lee, (2005), Adhikari and Chen, (2012), Jebli and Youssef (2015) have mentioned cases like this; the research should apply the Error Correction Model (ECM) like Driscoll- Kraay standard errors estimations in the pooled OLS model. Driscoll and Kraay (1998) standard errors for coefficients estimated by pooled OLS/WLS or fixed-effects (within) regression. ...
This paper introduces a robust empirical investigation on Triple Helix, Quadruple Helix, and their key drivers. The research questions are (i) how are Triple and Quadruple Helix models characterized in general and in the context of ASEAN-5? (ii) How effective are the relationships among the actors of different helixes in this region? The panel econometric analysis with cross-sectional dependence (CD) test is used to investigate the relationship and coevolution patterns within these. The empirical analysis employs innovation indicators of five founding ASEAN countries, namely Malaysia, Indonesia, Singapore, the Philippines, and Thailand, for the period 2000-2015, from an existing WDI, GEM and
... This technique is prevalently utilized on the grounds that the asymptotic dissemination is standard ordinary, rather than the non-typical asymptotic circulations ( Baltagi, 2004). Panel unit root test is recently one of the most popular tests because of its higher power compared to the unit root tests for individual time series ( Adhikari& Chen, 2012). The test for unit roots is conducted using three panel based methodologies proposed by Levin et al. (2002), hence alluded to as LLC. ...
The relationship and causality direction between electricity consumption and economic growth is an important issue in the fields of energy economics and policies towards energy use. Extensive literatures has discussed the issue, but the array of findings provides anything but consensus on either the existence of relations or direction of causality between the variables. This study extends research in this area by studying the long-run and causal relations between economic growth, electricity consumption, labour and capital based on the neo-classical one sector aggregate production technology mode using data of electricity consumption and real GDP for ASEAN from the year 1983 to 2012. The analysis is conducted using advanced panel estimation approaches and found no causality in the short run while in the long-run, the results indicate that there are bidirectional relationship among variables. This study provides supplementary evidences of relationship between electricity consumption and economic growth in ASEAN.
... This technique is prevalently utilized on the grounds that the asymptotic dissemination is standard ordinary, rather than the non-typical asymptotic circulations ( Baltagi, 2004). Panel unit root test is recently one of the most popular tests because of its higher power compared to the unit root tests for individual time series ( Adhikari& Chen, 2012). The test for unit roots is conducted using three panel based methodologies proposed by Levin et al. (2002), hence alluded to as LLC. ...
The relationship and causality direction between electricity consumption
and economic growth is an important issue in the fields of energy
economics and policies towards energy use. Extensive literatures has
discussed the issue, but the array of findings provides anything but
consensus on either the existence of relations or direction of causality
between the variables. This study extends research in this area by
studying the long-run and causal relations between economic growth,
electricity consumption, labour and capital based on the neo-classical
one sector aggregate production technology mode using data of
electricity consumption and real GDP for ASEAN from the year 1983 to
2012. The analysis is conducted using advanced panel estimation
approaches and found no causality in the short run while in the long-run,
the results indicate that there are bidirectional relationship among
variables. This study provides supplementary evidences of relationship
between electricity consumption and economic growth in ASEAN.
... The obtained results suggest, on the one hand, that EC in Ecuador is an important input for predicting EG, but the inverse is not true. This result, which is the only one that can be compared with previous studies, agrees with most of those studies (e.g., Chontanawat et al., 2006;Adhikari and Chen, 2013;Pastén et al., 2015;Apergis and Payne, 2010). Such a result suggests that policy measures directed to encourage energy conservation would have negative effects on EG. ...
Energy consumption (EC) in Ecuador has increased significantly during the past five decades. This has negatively affected the financial position of the country because (1) large EC subsidies are provided in its internal market, and (2) Ecuador is mostly a crude oil exporter and oil-derivatives importer country. Here, I aim to determine the Granger causal relationship between EC and economic growth (EG) in Ecuador by analyzing aggregated and disaggregated data for 1970–2015. Vector autoregressive (VAR) models considering structural breaks are estimated, and Granger causality tests are performed. I found that, in Ecuador, the following occurs: (1) EC causes EG (with no feedback effect) and is caused either directly or indirectly by the EG of its primary, secondary, and tertiary economic sectors; (2) oil and hydroelectricity consumption are the cause and the consequence, respectively, of EG; and (3) EC has a bi-directional causality relationship with transportation sector EG. Finally, for Ecuador to achieve more sustainable development dynamics, I recommend raising the price of oil-based energy (especially when it is used for unproductive activities) while subsidizing the consumption of renewable energy (specially oriented to the industrial sector).
... The energy-led growth hypothesis implies that a decrease in the energy supply will lead to an economic downturn; hence, countries should continue to invest in energy sectors to boost their economies. Studies that find empirical evidence supporting the energy-led growth hypothesis include Adhikari and Chen (2012), Tang and Shahbaz (2013), and Rezitis and Ahammad (2015). ...
The purpose of this study is to examine the relationships between tourism development, renewable energy consumption, and economic growth in the United States, France, Spain, China, Italy, Turkey, and Germany using an innovative bootstrap panel Granger causality model. The results show that tourism development and economic growth are interdependent in Germany; whereas tourism development induces economic growth in China and Turkey, the reverse is true in Spain. Causal relationships between renewable energy and economic growth give credence to theories of renewable energy-led growth in Spain and growth-led renewable energy in China, Turkey, and Germany. Whereas the Italian and U.S. models demonstrate a bidirectional relationship, the Spanish, Italian, Turkish, and U.S. data show a causal link stemming from tourism development. Theoretical and policy implications are discussed within the realm of macroeconomics and sustainability.
This study investigated how international tourism is impacting on environmental quality and renewable energy use in Africa, and how governance institutions on the continent are moderating these relationships. We employed the system GMM technique with a panel of 31 African economies from 2011 to 2020. We find that while international tourism is not a significant driver of environmental quality in Africa, it is significantly hampering renewable energy use on the continent. We also find that even though the unconditional effects of governance institutions on environmental quality are predominantly muted, their moderation role in the tourism-environmental quality relationship indicates that they offer potent channels for enhancing the contribution of the tourism sector toward improved environmental quality in Africa. Our results further indicate that governance institutions in Africa are significantly hampering the use of renewable energy, while their moderation role on the tourism-renewable energy use relationship is mainly muted. These findings generally highlight the fact that Africa is yet to harness its tourism potentials, while simultaneously dealing with the challenge of weak governance institutions. Among others, we recommended that policymakers and leaders in Africa should work together to harness the tourism potentials of the region and improve the quality of governance institutions.
This study investigates the dynamic causal relationship between electricity consumption and economic growth in the East African Community (1990-2021). It seeks to interrogate the nature of relationship between electricity consumption and economic growth. The hypothesis used in this study include growth, conservation, feedback and neutral hypothesis.
It uses panel data estimation techniques, particularly the panel dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), panel non-linear autoregressive distributed lag (NARDL). The Panel augmented Dickey Fuller (ADF)-fisher and Levin, Lin & Chu (LLC), 2003, was used to test the unit root process. Dumitreschu-Hurlin (2012) and pairwise Granger tests were used to test for the direction of causality.
The findings indicate growth hypothesis with a unidirectional relationship running from electricity consumption to economic growth. Regional governments must increase their investments in electricity market trading to boost economic growth. Greater benefits from regional cooperation can be realized with increased investment in electricity consumption.
This is a novel study of the dynamic causal relationship between electricity consumption and economic growth in the East African Community. It is a ground-breaking inquiry into the possibility of integrating electricity markets and their role in promoting economic growth.
Throughout human history, energy has played a critical role in society’s development. Many people believe that energy consumption has a close relationship with economic growth. We created a simple regression model to verify this assumption. We also compared fossil and renewable energy to see if there is a different impact on high-income compared fossil and renewable energy to see if there is a different impact on high-income and low-income countries. As a result, we found that energy consumption doesn’t have a strong relationship with high-income countries, and it has a negative relationship with low-income countries. Due to this finding, we conclude that energy consumption does not typically represent economic growth as people used to believe, and it should not be seen as a symbol that indicates a country’s development.
This study examines the relationship between energy consumption (EC) and economic growth (GDP) for a sample of 14 MENA countries during the period 1980-2017. These countries are divided into two groups: Group of Energy Exporting Countries (OPEC countries). And a group of poor countries in terms of energy sources (the rest of the countries). by using recently developed panel co-integration techniques. We adopt a four-stage approach, consisting of panel unit root, panel co-integration, Granger causality and estimate the kuznets curve between the two variables. The results showed that GDP and energy consumption move together in the long-run. By estimating these long-run relationships and testing for causality using panel co-integration techniques. We found bidirectional causality between energy consumption and economic growth. Finally, we estimated the Kuznets curve between the two studied variables, as we found that the curve hypothesis is fulfilled in the case of the countries combined, and in the case of the energy-exporting countries (involved in the OPEC), While it is different for other countries.
An Autoregressive Distributed Lag (ARDL) model and panel techniques were used to analyze the long-run and the short-run relationship between energy poverty and economic growth for nine Latin American countries for the period 1990-2018. The panel data analysis results confirmed cointegration between the variables, supporting the relevance of energy poverty for economic development in the studied countries. From an ARDL Pooled Mean Group (PMG) estimation, a significant effect from energy poverty to economic development, in the long run, is proved, meaning that improvements in energy access led to increases in economic growth. The long-run homogeneity among countries could imply that, in the long term, political measures to overcome energy poverty should be adopted and coordinated in a homogeneous manner throughout the Latin American studied region while in the short-run, particular country policies are needed to increase levels of energy access. Then, according to the empirical evidence, public and private institutions need to implement initiatives to overcome energy poverty by promoting equal access to reliable, sustainable, accessible, healthy, and sufficient energy, and coordinated efforts in the region could lead to stronger results in the long run.
This present study is the first attempt to analyze the synergy between primary energy consumption, economic growth, natural resources, quality of government, financial development, and gross capital formation in the panel data of 30 developing countries from 1990 to 2017. For this purpose, the study employed pooled regression, fixed effects, random effects, and the heterogeneous panel Dumitrescu-Hurlin causation procedure. Our findings confirm that primary energy consumption, gross capital formation, financial development, and quality of government positively impact economic growth. The heterogeneous panel causality test confirms the feedback effect hypothesis in the connection between primary energy consumption and other factors including economic growth. These results offer new insights into policy implications for the developing countries being studied.
Green energy projects (including wind, solar, biomass, hydro projects) are the major constituents of biofuel
projects and primary need of global world which are directly concerned with economic growth and gross domestic products (GDP) development. In last few decades, fossil fuel consumption and carbon dioxide (CO2)
emission have been increased due to more economic growth and growing population. Moreover, the objective of
this research is to assess the consequence of biofuel including natural gas, environmentally friendly power
projects (renewable-energy), and thermal power utilization on financial turn of events including GDP and CO2 in
ten top countries. Multivariate climate countries with ubiquitous CO2 emission during the period of 1990–2018
were selected to examine the long-run flexibility as well as the path of causality between different variables, the
panel co-integration test, panel heterogonous Dumitrescu and Hurlin causality evaluation and panel completely
modified ordinary least squares were employed. The panel co-reconciliation test verify that variables have a
long-run equilibrium correlation in their relationships. Long haul versatility and causality tests show that natural
gas doesn’t add to financial development or CO2 decreases. According to this present study, results can help to
develop conservative policies regarding long-run and sustainable energy and design in energy development
This study is a meta-analytic investigation of energy consumption and economic growth. It makes a literature survey on the dynamic causal relationship between broad variables of energy and economic growth for the period 1974–2021. The objective of this study is to investigate stationarity, cointegration and direction of causality between energy consumption and economic growth. It uses survey methods to profile related literature of the energy consumption–economic growth nexus. It tests four established hypotheses, feedback, growth, conservation and neutrality. It concentrates on both country as well as multi-country panel based studies. The variables chosen, econometric as well as theoretical models, time periods has contributed to the increased level of disagreement. The results are thoroughly mixed with no agreement, some studies are explicit on the degree to which results are contentious. There is no consensus for both country specific as well as panel based studies. On the whole the growth hypothesis is the most dominant outcome for country based studies. Our findings indicate that this debate is inconclusive with growth hypothesis accounting for 43.8%, feedback 18.5%, conservation 27.2%, and neutrality hypothesis 10.5% for country specific studies. This study gives a footprint of the state of the art and stimulates the level of debate for researchers on energy consumption and economic growth.
This study aims to examine the relationship between the non-renewable energy consumption of the countries and their economic status since energy consumption and production appear to be interconnected phenomena. This study analyses the Eastern, Middle, North, South, and Western regions of the European continent from 1990 to 2014. To the best of our knowledge, this is the first paper to analyze the relationship between non-renewable energy consumption and economic growth in the European continent by region. The study adopts a panel causality process to examine the relationship between two phenomena. According to the empirical analyses, there is bidirectional causality between non-renewable energy consumption and economic growth in Eastern, Middle, North, and South European regions whereas a unidirectional relationship from non-renewable energy consumption to economic growth in the Western. Non-renewable energy consumption and economic growth are still interconnected phenomena in the European countries even though climate concerns, environmental precautions, and promotion to reduce unsustainable production.
In this study, the relation between economic growth and energy consumption are tested based on hypothesis within mainstream growth theories in selected emerging markets.Matching mainstream growth theory, namely explaining the relation between two factors, is explained based on the results of Bootstrap Granger Causality test of Konya.According to both cross-sectional and panel results, the protectionism hypothesis claiming a significant causality in the direction of economic growth to energy consumption is confirmed.These results can be explained with their own specific fundamental characteristics of emerging market economies.The population of emerging market countries makes more than a half of the world population and they demonstrate higher growth rates than developed, industrialized countries.Along with the increasing degree of urbanization and the urbanization of rural areas as a result of fast growing sectoral activities such as manufacturing, technology and software, the energy consumption may lead to these increases. Actually, other than India case, we couldn’t find a causality relation in both direction in selected emerging countries.The empirical results shows that only in India the energy consumption leads to economic growth and vice versa, and support the feedback hypothesis.The bidirectional causality between variables may be due to a positive relationship between manufacturing and growth, planning 74% of the development projects as energy related projects within the framework of 2030 Sustainable Development Goals, innovation efforts in energy related technologies, and prioritizing diversification of energy supplies.Nonetheless, we couldn’t find any causality in the direction from energy consumption to economic growth in Hungary, Malaysia, China, Turkey, Mexico, Argentina, Romania and Brazil.This result may stem from energy dependency of these countries in terms of energy resources, which leads to an increase in energy imports and instability in economic growth when energy consumption increases.In this study, the importance of energy consumption for economic growth in emerging market economies with distinguishing rate of economic growth is analyzed, and it’s concluded that there is no direct effect of energy consumption on growth.
Using panel data covering the period 1989-2016 for BRICS countries, this study applied the pooled regression, fixed effects and random effects models in an attempt to analyze the impact of energy use and real per capita income on CO 2 emissions amongst the BRICS countries. Post-estimation diagnostic tests revealed that the fixed effects model was the most appropriate model and that it was not suffering from serial correlation and cross-sectional dependence. The results of the study indicated that both real income and energy use have a positive and significant impact on carbon dioxide emissions among the BRICS member countries over the period under consideration. This is in line with the hypothesis of the Environmental Kuznets Curve which postulates a positive relationship between income growth and carbon dioxide emissions in the growth of economies in the short run. Relevant policy prescriptions have been put forward for consideration by BRICS governments.
This paper is a contribution to the ongoing debate over whether there is a relationship between energy consumption and economic growth. Although the ECOWAS member countries are among the countries that are facing interrelated challenges of energy access, energy security and environmental degradation in the world, but little attention has been paid to their energy consumption-growth nexus. Therefore, this study empirically investigates the dynamic relationship between energy consumption and economic growth in 14 ECOWAS countries from 2004 to 2013 through the application of fixed-effect, random effect model, and Arrelano and Bond GMM estimator. Results show a positive impact of energy consumption on economic growth of the investigated economies. Thus, the study recommends that energy efficiency should be improved in order to raise the standard of living for ECOWAS populations. This can be achieved by reducing energy bills which in turn make access to energy more affordable and easier to attain, both in urban and rural areas of the region.
The study tests the validity of the environmental Kuznets curve (EKC) for SAARC countries by using closed and open economy Models. The Peroni Panel Cointegration technique along with FMOLS estimation techniques have been used for empirical analysis by using the data from 1972-2015. The long run and short run estimates of the closed economy model reveals positive and significant relationship between Per capita GDP, per capita GDP2 and the carbon emissions that deny the existence of EKC. The findings of open economy model signify that FDI not only helps to transfer cleaner technologies, but it enables the producers to use less pollutant technologies for the production purposes. Moreover, an increase in the forest area is helpful for reducing the carbon emissions. Finally, population density and energy consumption are proved significant contributors of carbon emissions. The study suggests that effective policies should be followed for reducing emissions, regulating FDI-environment and per capita GDP environment relationship.
The study tests the validity of the environmental Kuznets curve (EKC) for SAARC countries by using closed and open economy Models. The Peroni Panel Cointegration technique along with FMOLS estimation techniques have been used for empirical analysis by using the data from 1972-2015. The long run and short run estimates of the closed economy model reveals positive and significant relationship between Per capita GDP, per capita GDP2 and the carbon emissions that deny the existence of EKC. The findings of open economy model signify that FDI not only helps to transfer cleaner technologies, but it enables the producers to use less pollutant technologies for the production purposes. Moreover, an increase in the forest area is helpful for reducing the carbon emissions. Finally, population density and energy consumption are proved significant contributors of carbon emissions. The study suggests that effective policies should be followed for reducing emissions, regulating FDI-environment and per capita GDP environment relationship.
The relationship between energy consumption and economic growth has been analyzed by a number of previous studies. However, a consensus has not been reached to define the relationship between the variables. This paper aims to analyze the relationship between energy consumption and economic growth for six Asian countries viz. China, India, Indonesia, Malaysia, Philippines and Thailand by employing statistical and econometric techniques such as ARDL model, Johansen's Co integration test, VECM, VAR and Toda Yamamoto causality test. Results indicate that energy consumption and economic growth are co integrated in the long run in case of China, India and Indonesia however VECM indicates that both variables are unable to correct itself towards equilibrium after a shock when energy consumption is the independent variable and Real GDP the dependent variable. Co integration does not exist in case of Malaysia, Philippines and Thailand and VAR indicates that GDP is affect by its past values at lag 1 for Malaysia and Thailand and GDP is affected by its past values at lag 1 and 2 for Philippines. In case of India and Thailand there exists a uni-directional causal relationship running from GDP to energy consumption.Keywords: Energy consumption, Economic growth, Co integration, ARDL, Toda Yamamoto Causality.JEL Classifications: P18, Q43DOI: https://doi.org/10.32479/ijeep.9678
The cost of power system rationing, which is a crucial parameter for determining optimal resilience investments, is usually estimated using reduced-form linear models or ordinary input-output analysis. However, such methods do not properly address either consumers’ rational reactions to rationing policy or policy design nonlinearities. To solve this problem, this paper estimates the effects of power system rationing using a general equilibrium model. The model solution shows that the power cut distribution among industries is a critical variable for quantifying policy effects and provides insights into optimal policy design.
The objective of the research is to identify the impact of innovation and supply , transformation and consumption of electricity on economic development. In order to analyse the relationship between economic growth, innovation and energy consumption in EU countries, the regression technique was used. The output variable is Gross Domestic Product per capita computed for 26 countries across the EU. The explanatory variables are the potential factors that could have contribution to GDP growth of countries, as well as the innovation-measured by Global Innovation Index and Primary Energy Consumption. The result of research can be used in substantiation of public policies designed to boost the economic development of various countries.
The paper has studied the change in the electric intensity of the Russian economy over the past 25 years. Equations have been constructed that correlate the electricity consumption with GDP (GVA for key economic sectors) and investment volume. The influence of structural changes and power consumption in particular sectors, as well as the modernization of the key economic sectors on the dynamics of the Russian economy electric intensity, has been identified.
ÖZET
Çalışmada 1990 ile 2014 dönemi arasında enerji tüketimi ve ekonomik büyüme arasındaki zamansal nedensellik ilişkisi incelenmektedir. Pesaran vd. (2001) tarafından geliştirilen ARDL sınır testi çalışmada kullanılmıştır. Enerji tüketimi değişkeni olarak kişi başına toplam enerji tüketimi ve ekonomik büyüme değişkeni olarak da kişi başına düşen gayrisafi yurtiçi hasıla verisi kullanılarak analiz yapılmıştır. ARDL sınır testi sonuçlarına göre enerji tüketimi ve ekonomik büyüme arasında uzun dönemli istikrarlı bir ilişki tespit edilmiştir. Nedensellik testi sonuçlarına bakıldığında ise toplam enerji tüketiminden ekonomik büyümeye doğru tek yönlü bir nedensellik tespit edilmiştir. Genel olarak araştırma enerji tüketiminin Türkiye’de ekonomik büyümeye neden olduğu sonucuna ulaşmıştır.
Anahtar Kelimeler: Türkiye, Enerji Tüketimi, Ekonomik Büyüme
Jel Kodları: Q43, O40, O47
ÖZET
Çalışmada 1990 ile 2014 dönemi arasında enerji tüketimi ve ekonomik büyüme arasındaki zamansal nedensellik ilişkisi incelenmektedir. Pesaran vd. (2001) tarafından geliştirilen ARDL sınır testi çalışmada kullanılmıştır. Enerji tüketimi değişkeni olarak kişi başına toplam enerji tüketimi ve ekonomik büyüme değişkeni olarak da kişi başına düşen gayrisafi yurtiçi hasıla verisi kullanılarak analiz yapılmıştır. ARDL sınır testi sonuçlarına göre enerji tüketimi ve ekonomik büyüme arasında uzun dönemli istikrarlı bir ilişki tespit edilmiştir. Nedensellik testi sonuçlarına bakıldığında ise toplam enerji tüketiminden ekonomik büyümeye doğru tek yönlü bir nedensellik tespit edilmiştir. Genel olarak araştırma enerji tüketiminin Türkiye’de ekonomik büyümeye neden olduğu sonucuna ulaşmıştır.
Anahtar Kelimeler: Türkiye, Enerji Tüketimi, Ekonomik Büyüme
Jel Kodları: Q43, O40, O47
By using the Emirmahmutoglu–Kose bootstrap Granger non-causality method, this study
explores the directions of causality among tourist arrivals, tourism receipts, energy consumption
and economic growth for the top 10 most-visited countries (France, the USA, Spain, China, Italy,
Turkey, Germany, the United Kingdom, Russia, and Mexico) in the world. This study finds a variety
of causal directions between the pair of analyzed variables for each country and the panel. Since
cross-sectional dependence exists across the top countries for the analyzed variables, the bootstrap
Granger causality test that accounts for the mentioned issue in the estimation process presumably
produces reliable and accurate outputs. Further results and policy implications are discussed in this
empirical study.
By using the Pedroni and Kao panel co-integration techniques, and FMOLS, DOLS and OLS methods, this study explores the long-run relationship among tourism receipts, renewable energy consumption and economic growth for the European Union countries. The long-run estimators report that " renewable energy increases economic growth " , " tourism receipts increase economic growth " , " capital increases economic growth " and " labor force increases economic growth ". Further results and some policy implications are discussed in this empirical study.
In this chapter we study the asymptotic distributions for ordinary least squares (OLS), fully modified OLS (FMOLS), and dynamic OLS (DOLS) estimators in cointegrated regression models in panel data. We show that the OLS: FMOLS, and DOLS estimators are all asymptotically normally distributed. However; the asymptotic distribution of the OLS estimator is shown to have a non-zero mean. Monte Carlo results illustrate the sampling behavior of the proposed estimators and show that (I) the OLS estimator has a non-negligible bias in finite samples, (2) the FMOLS estimator does not improve over the OLS estimator in general, and (3) the DOLS outperforms both the OLS and FMOLS estimators.
The aim of this paper is to provide new empirical evidence on the relationship between energy consumption and economic growth for 21 African countries over the period from 1970 to 2006, using recently developed panel cointegration and causality tests. The countries are divided into two groups: net energy importers and net energy exporters. It is found that there exists a long-run equilibrium relationship between energy consumption, real GDP, prices, labor and capital for each group of countries as well as for the whole set of countries. This result is robust to possible cross-country dependence and still holds when allowing for multiple endogenous structural breaks, which can differ among countries. Furthermore, we find that decreasing energy consumption decreases growth and vice versa, and that increasing energy consumption increases growth, and vice versa, and that this applies for both energy exporters and importers. Finally, there is a marked difference in the cointegration relationship when country groups are considered.
The causal relationship which Kraft and Kraft, Chow and Fisher, Sims and others identify for gross energy consumption (GEC) and gross national product (GNP) is challenged. At issue is the significance of data during periods of war and the discrepency between observed variables and the time delay from cause to effect. No solution is advanced for determining causal relationship. 14 references, 3 tables. (DCK)
Energy is a crucial component to economic growth and plays a vital role in economic
development. This study inquires the causal relationships between energy consumption
(EC) and the economic growth (EG) within a multivariate framework that includes capital
stock and labor input for the panel of three SAARC countries by using modern panel unit
root technique, residual based panel cointegration and panel based error correction models
.The empirical results fully support a cointegration relationship between EC and EG in the
long run. But from the causal point of view there is long run unidirectional causality
running from EC to EG and no causality was found in the short run.
This paper aims to investigate the relationship between energy consumption and economic growth for 11 East Asian countries over the period 1971-2005 by taking into account their strong relationships. Based on fully modified ordinary least squares (FMOLS) and dynamic OLS (DOLS) approaches, while there exists a strong relation running from economic growth to energy consumption, it is observed that the strong relationship which runs from energy consumption to economic growth is overwhelmingly rejected for all cases except Indonesia and the Philippines. Moreover the inverse relation between two variables is observed for these two countries.
This paper examines the long-run relationship between energy consumption and real GDP, including energy prices, for 25 OECD countries from 1981 to 2007. The distinction between common factors and idiosyncratic components using principal component analysis allows to distinguish between developments on an international and a national level as drivers of the long-run relationship. Indeed, cointegration between the common components of the underlying variables indicates that international developments dominate the long-run relationship between energy consumption and real GDP. Furthermore, the results suggest that energy consumption is price-inelastic. Causality tests indicate the presence of a bi-directional causal relationship between energy consumption and economic growth.
This paper develops unit root tests for panel data. These tests are devised under more general assumptions than the tests previously proposed. First, the number of groups in the panel data is assumed to be either finite or infinite. Second, each group is assumed to have different types of nonstochastic and stochastic components. Third, the time series spans for the groups are assumed to be all different. Fourth, the alternative where some groups have a unit root and others do not can be dealt with by the tests. The tests can also be used for the null of stationarity and for cointegration, once relevant changes are made in the model, hypotheses, assumptions and underlying tests. The main idea for our unit root tests is to combine p-values from a unit root test applied to each group in the panel data. Combining p-values to formulate tests is a common practice in meta-analysis. This paper also reports the finite sample performance of our combination unit root tests and Im et al.'s [Mimeo (1995)] t-bar test. The results show that most of the combination tests are more powerful than the t-bar test in finite samples. Application of the combination unit root tests to the post-Bretton Woods US real exchange rate data provides some evidence in favor of the PPP hypothesis.
This paper proposes a residual-based Lagrange Multiplier (LM) test for the null of cointegration in panel data. The test is analogous to the locally best unbiased invariant (LBUI) for a moving average (MA) unit root. The asymptotic distribution of the test is derived under the null. Monte Carlo simulations are performed to study the size and power properties of the proposed test. Overall, the empirical sizes of the LM- FM and LM-DOLS are close to the true size even in small samples. The power is quite good for the panels where T >50, and decent with panels for fewer observations in T. In our fixed sample of N=50 and T=50, the presence of a moving average and correlation between the regressor errors and regressors causes the two tests to perform quite differently, complicating the choice of estimation procedures. In general, the LM- DOLS test seems to be better at correcting these effects, although in some cases the LM-FM test is more powerful. Although much of the non- stationary time series econometrics has been criticized for having more to do with the specific properties of the data set rather than underlying economic models, the recent development of the cointegration literature has allowed for a concrete bridge between economic long run theory and time series methods. Our test now allows for the testing of the null of cointegration in a panel setting and should be of considerable interest to economists in a wide variety of fields.
This paper applies panel unit root, panel cointegration, and panel causality techniques to re-examine the total energy and electricity demand functions of 25 selected OECD countries during the 1978-2004 period. The panel results indicate that total energy demand is income inelastic and price inelastic, whereas electricity demand is income elastic and price inelastic. Based on the results of the panel causality test, there are reciprocal causal relationships among real income, real energy price, and total energy consumption. Furthermore, a uni-directional causality runs from income and electricity price to electricity onsumption. The results for the panel as a whole suggest that the demand for total energy and electricity in the OECD countries is driven largely by strong economic growth, while consumers are largely insensitive to price changes.
This study tests the relationship between energy consumption and economic growth in Sub-Saharan Africa, using a panel co-integration approach. Country-level time series data of energy consumption and economic growth are pooled and used to estimate the model. Sub-Saharan African countries in the sample are classified into low income and middle income countries. The findings support the neutrality hypothesis in the short-run, except for middle income countries, and a strong causation running in both directions is found in the long-run. The different results for low and middle income countries provide evidence of the importance of income level in the causal relationship. This study helps to explain the interdependence of energy consumption and economic growth in Sub-Saharan Africa. Results are critical in formulating sustainable development policies that are geared to the efficient allocation of resources which are expected to increase access to energy services in the study region.
This paper investigates the long-run and the causal relationship between greenhouse gas emissions, energy consumption and economic growth for Canadian industrial sectors over the period 1990–2007. The empirical findings suggest that in the long-run equilibrium, energy consumption has a positive and statistically significant impact on greenhouse gas emissions whereas a non-linear relationship is found between greenhouse gas emissions and economic growth, consistent with the environmental Kuznets curve. The short-run dynamics conveys that there is a unidirectional Granger causality running from energy consumption to greenhouse gas emissions; from economic growth to greenhouse gas emissions and a weak unidirectional causality running from greenhouse gas emissions to energy consumption; from economic growth to energy consumption. In the long-run however, there seems to be a weak one way causality flowing from energy consumption and economic growth to greenhouse gas emissions.
This note reports results of an empirical test for determining the causal relationship between energy and gross national product. According to a current view, there is a constant and unchanging relationship between gross energy consumption and GNP. A logical corollary is that energy conservation is an unacceptable policy option since it would adversely influence economic activity. This implies that the direction of causality runs from energy to GNP as well as the other way around. With regard to the issue of causation, Sims (J. Am. Statis. Assn., Mar 1972) developed a test for unidirectional causality, which he applied to test the existence of a causal relationship between money and GNP. In this note, the authors attempt to determine both the empirical relationship between gross energy inputs and GNP and the presence of a causal link between these variables. The main empirical finding is that causality is unidirectional, only running from GNP to energy for the postwar period, and there is no causality from energy to GNP.
This chapter uses fully modified OLS principles to develop new methods for estimating and testing hypotheses for cointegrating vectors in dynamic panels in a manner that is consistent with the degree of cross sectional heterogeneity that has been permitted in recent panel unit root and panel cointegration studies. The asymptotic properties of various estimators are compared based on pooling along the 'within' and 'between' dimensions of the panel. By using Monte Carlo simulations to study the small sample properties, the group mean estimator is shown to behave well even in relatively small samples under a variety of scenarios.
This paper applies the panel unit root, heterogeneous panel cointegration and panel-based dynamic OLS to re-investigate the co-movement and relationship between energy consumption and economic growth for 30 provinces in mainland China from 1985 to 2007. The empirical results show that there is a positive long-run cointegrated relationship between real GDP per capita and energy consumption variables. Furthermore, we investigate two cross-regional groups, namely the east China and west China groups, and get more important results and implications. In the long-term, a 1% increase in real GDP per capita increases the consumption of energy by approximately 0.48-0.50% and accordingly increases the carbon dioxide emissions by about 0.41-0.43% in China. The economic growth in east China is energy-dependent to a great extent, and the income elasticity of energy consumption in east China is over 2 times that of the west China. At present, China is subject to tremendous pressures for mitigating climate change issues. It is possible that the GDP per capita elasticity of carbon dioxide emissions would be controlled in a range from 0.2 to 0.3 by the great effort.
The goal of this paper is to examine the long-run elasticities of the impacts of energy consumption on GDP and GDP on energy consumption. The energy consumption-GDP relationship is amongst the most popular relationships examined in the energy economics literature. The bulk of the extant literature has assumed a positive relationship between energy consumption and real GDP. Our analysis shows that in only around 60% of the countries considered the relationship is positive.
This paper applies the most recently developed panel unit root, heterogeneous panel cointegration and panel-based error correction models to re-investigate co-movement and the causal relationship between energy consumption and real GDP within a multivariate framework that includes capital stock and labor input for 16 Asian countries during the 1971–2002 period. It employs the production side model (aggregate production function). The empirical results fully support a positive long-run cointegrated relationship between real GDP and energy consumption when the heterogeneous country effect is taken into account. It is found that although economic growth and energy consumption lack short-run causality, there is long-run unidirectional causality running from energy consumption to economic growth. This means that reducing energy consumption does not adversely affect GDP in the short-run but would in the long-run; thus, these countries should adopt a more vigorous energy policy. Furthermore, we broaden the investigation by dividing the sample countries into two cross-regional groups, namely the APEC and ASEAN groups, and even more important results and implications emerge.
This paper uses the panel data of energy consumption (EC) and economic growth (GDP) for 51 countries from 1971 to 2005. These countries are divided into three groups: low income group, lower middle income group and upper middle income group countries. Firstly, a relationship between energy consumption and economic growth is investigated by employing Pedroni (1999) panel cointegration method. Secondly, panel causality test is applied to investigate the way of causality between the energy consumption and economic growth. Finally, we test whether there is a strong or weak relationship between these variables by using Pedroni (2001) method. The empirical results of this study are as follows: i) Energy consumption and GDP are cointegrated for all three income group countries. ii) The panel causality test results reveal that there is long-run Granger causality running from GDP to EC for low income countries and there is bidirectional causality between EC and GDP for middle income countries. iii) The estimated cointegration factor, β, is not close to 1. In other words, no strong relation is found between energy consumption and economic growth for all income groups considered in this study. The findings of this study have important policy implications and it shows that this issue still deserves further attention in future research.
In this paper, we examine the intertemporal causal relationship between energy consumption and economic growth in Tanzania during the period of 1971–2006. Unlike the majority of the previous studies, we employ the newly developed autoregressive distributed lag (ARDL)-bounds testing approach by Pesaran et al. [2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics 16, 289–326] to examine this linkage. We also use two proxies of energy consumption, namely total energy consumption per capita and electricity consumption per capita. The results of the bounds test show that there is a stable long-run relationship between each of the proxies of energy consumption and economic growth. The results of the causality test, on the other hand, show that there is a unidirectional causal flow from total energy consumption to economic growth and a prima-facie causal flow from electricity consumption to economic growth. Overall, the study finds that energy consumption spurs economic growth in Tanzania.
This paper investigates the causal relationship between aggregated and disaggregated levels of energy consumption and economic growth for Greece for the period 1960–2006 through the application of a later development in the methodology of time series proposed by Toda and Yamamoto (1995). At aggregated levels of energy consumption empirical findings suggest the presence of a uni-directional causal relationship running from total energy consumption to real GDP. At disaggregated levels empirical evidence suggests that there is a bi-directional causal relationship between industrial and residential energy consumption to real GDP but this is not the case for the transport energy consumption with causal relationship being identified in neither direction. The importance of these findings lies on their policy implications and their adoption on structural policies affecting energy consumption in Greece suggesting that in order to address energy import dependence and environmental concerns without hindering economic growth emphasis should be put on the demand side and energy efficiency improvements.
The Pacific Island countries are small island economies that are increasingly dependent on energy for growth and development, yet highly susceptible to climate change. Thus, the relationship between energy consumption and GDP is crucial for realizing their future development and growth objectives. This article tests for Granger causality and provides long-run structural estimates for the relationship between energy consumption, GDP and urbanization for a panel of Pacific Island countries. For the panel as a whole in the long-run there is bidirectional Granger causality between energy consumption and GDP and these variables exert a positive impact on each other. A 1% increase in energy consumption increases GDP by 0.11%, while a 1% increase in GDP increases energy consumption by 0.23%. The findings suggest that for the panel as a whole these countries should increase investment in energy infrastructure and regulatory reform of energy infrastructure to improve delivery efficiency, continue to promote alternative energy sources and put in place energy conservation policies to reduce unnecessary wastage. These strategies seek to realize the dual objectives of reducing the adverse effects of energy use on the environment, while avoiding the negative effect on economic growth of reducing energy consumption.
This paper applies a recent advance in panel analysis to estimate the panel cointegration and panel vector error correction models for a set of 22 OECD countries using annual data covering the period 1960–2001. We investigate the relationship between energy consumption and income using an aggregate production function and controlling for the capital stock, as well as by exploring the dynamic directions of the causality among these three variables. We firstly obtain solid and convincing evidence of a fairly strong long-run equilibrium relationship among them. Secondly, it is found that the capital stock is much more productive than energy consumption. Third, it is observed that neglecting the impact of the capital stock on income tends to overestimate the effect of energy consumption. Finally, the panel causality test shows bi-directional causal linkages exist among energy consumption, the capital stock and economic growth. Overall, the findings reveal that the capital stock plays a critical role in realizing the dynamic relationship between energy and income.
In this paper we re-investigate the co-movement and the causality relationship between energy consumption and GDP in 18 developing countries, using data for the period 1975 to 2001. Recently developed tests for the panel unit root, heterogeneous panel cointegration, and panel-based error correction models are employed. The empirical results provide clear support of a long-run cointegration relationship after allowing for the heterogeneous country effect. The long-run relationship is estimated using a full-modified OLS. The evidence shows that long-run and short-run causalities run from energy consumption to GDP, but not vice versa. This result indicates that energy conservation may harm economic growth in developing countries regardless of being transitory or permanent.
The causal relationship between energy consumption and economic growth is investigated applying two multivariate time series models: a demand side model of energy, GDP and real energy price and a production side model of GDP, energy, capital, and labor. To test for Granger causality in the presence of cointegration among the variables, we employ a VECM rather than a VAR model. Empirical results from the two models for Korea over the period 1981:1–2000:4 suggest no causality between energy and GDP in the short run and a unidirectional causal relationship running from GDP to energy in the long run. It implies an energy conservation policy may be feasible without compromising economic growth in the long run. It also implies that a sustainable development strategy may be feasible with lower level of CO2 emissions from fossil fuel combustion.
This paper examines the causality issue between energy consumption and GDP for South Korea and Singapore, with the aid of cointegration and error-correction modeling. Results of the cointegration and error-correction models indicate bidirectional causality between GDP and energy consumption for both South Korea and Singapore. However, results of the standard Granger causality tests show no causal relationship between GDP and energy consumption for South Korea and unidirectional causal relationship from energy consumption to GDP for Singapore.
This paper examines the relationship between capital formation, energy consumption and real GDP in a panel of G7 countries using panel unit root, panel cointegration, Granger causality and long-run structural estimation. We find that capital formation, energy consumption and real GDP are cointegrated and that capital formation and energy consumption Granger cause real GDP positively in the long run. We find that a 1% increase in energy consumption increases real GDP by 0.12–0.39%, while a 1% increase in capital formation increases real GDP by 0.1–0.28%.
This paper estimates the causal relationships between energy consumption and income for India, Indonesia, the Philippines and Thailand, using cointegration and error-correction modelling techniques. The results indicate that, in the short-run, unidirectional Granger causality runs from energy to income for India and Indonesia, while bidirectional Granger causality runs from energy to income for Thailand and the Philippines. In the case of Thailand and the Philippines, energy, income and prices are mutually causal. The study results do not support the view that energy and income are neutral with respect to each other, with the exception of Indonesia and India where neutrality is observed in the short-run.
This paper reexamines the inter-temporal link between energy consumption and income in six developing countries with diverse economic backgrounds and energy statistics, in a production function framework. We employ the generalized variance decompositions and generalized impulse response techniques to see if the growth of income and energy consumption contains considerable information to predict each other. In all countries, energy appears as an essential factor of production. Results indicate that energy may be a relatively more important input than labor and/or capital in some countries. Hence, neutrality of energy does not seem to hold.
Using a neo-classical one-sector aggregate production technology where capital, labor and energy are treated as separate inputs, this paper develops a vector error-correction (VEC) model to test for the existence and direction of causality between output growth and energy use in Canada. Using the Johansen cointegration technique, the empirical findings indicate that the long-run movements of output, labor, capital and energy use in Canada are related by two cointegrating vectors. Then using a VEC specification, the short-run dynamics of the variables indicate that Granger-causality is running in both directions between output growth and energy use. Hence, an important policy implication of the analysis is that energy can be considered as a limiting factor to output growth in Canada.
This work investigates the causality relationship between gross domestic product (GDP) and energy consumption in the six countries of the Gulf Cooperation Council (GCC). Recently developed panel cointegration and causality techniques are used to uncover the direction of energy–GDP causality in the GCC. Empirical results indicate a unidirectional causality running from GDP to energy consumption. Evidence shows no support for the hypothesis that energy consumption is the source of GDP growth in the GCC countries. Such results suggest that energy conservation policies may be adopted without much concern about their adverse effects on the growth of GCC economies.
Several industrialized countries have signed the Kyoto Protocol, promising to reduce greenhouse gasses (GHG) emissions. To reduce or mitigate such emissions several policies including reducing energy consumption, increasing energy efficiency, decreasing energy intensity and forestation may be possible. The viability and effectiveness of each policy may differ due to country specific factors. This paper tries to assess the impact of a change in energy consumption on income and vice versa in G-7 countries. We employ multivariate cointegration, error correction models and generalized variance decompositions and uncover Granger causality relation between energy consumption and income in all countries. However, the direction of causality seems to differ across countries. This may suggest that although they are at the same level of economic development, different policy alternatives in support of the protocol may be available in each country.
A recently developed methodology of the cointegration test is employed to determine whether energy consumption has a long-run equilibrium relationship with the level of income or employment. It is found that the long-run equilibrium relationship fails to exist in either case. The finding implies a long-run neutrality of energy consumption, which is consistent with the short-run neutrality found in the literature. The results are further confirmed by splitting the sample into two sub-periods.
Unlike previous studies on the causal relationship between energy consumption and economic growth, this paper illustrates how the finding of cointegration (i.e. long-term equilibrium relationship) between these variables, may be used in testing Granger causality. Based on the most recent Johansen's multivariate cointegration tests preceded by various unit root or non-stationarity tests, we test for cointegration between total energy consumption and real income of six Asian economies: India, Pakistan, Malaysia, Singapore, Indonesia and the Philippines. Non-rejection of cointegration between variables rules out Granger non-causality and imples at least one way of Granger-causality, either unidirectional or bidirectionial. Secondly, by using a dynamic vector error-correction model, we then analyse the direction of Granger-causation and hence the within-sample Granger-exogeneity or endogeneity of each of the variables. Thirdly, the relative strength of the causality is gauged (through the dynamic variance decomposition technique) by decomposing the total impact of an unanticipated shock to each of the variables beyond the sample period, into proportions attributable to shocks in the other variables including its own, in the bivariate system. Results based on these tools of methodology indicate that while all pair-wise relationships shared common univariate integrational properties, only relationships for three countries (India, Pakistan and Indonesia) were cointegrated. For these countries, temporal causality results were mixed with unidirectional causality from energy to income for India, exactly the reverse for Indonesia, and mutual causality for Pakistan. The VDCs were not inconsistent with these results and provided us with an additional insight as to the relatively more dominant direction of causation in Pakistan. Simple bivariate vector-autoregressive models for the three non-cointegrated systems did not indicate any direction of causality, significantly in either direction.
Causal relationship between energy consumption and economic growth is investigated applying a multivariate model of capital, labor, energy and GDP. Usual BTU energy aggregate is substituted with a Divisia aggregate in an attempt to mitigate aggregation bias. To test for Granger causality in the presence of cointegration among the variables, we employ a vector error correction model rather than a vector autoregressive model. Empirical results for Korea over the period 1970–1999 suggest a long run bidirectional causal relationship between energy and GDP, and short run unidirectional causality running from energy to GDP. The source of causation in the long run is found to be the error correction terms in both directions.
World Development Indicators, the World Bank's respected statistical publication presents the most current and accurate information on global development on both a national level and aggregated globally. This information allows readers to monitor the progress made toward meeting the goals endorsed by the United Nations and its member countries, the World Bank, and a host of partner organizations in September 2001 in their Millennium Development Goals. The print edition of World Development Indicators 2005 allows you to consult over 80 tables and over 800 indicators for 152 economies and 14 country groups, as well as basic indicators for a further 55 economies. There are key indicators for the latest year available, important regional data, and income group analysis. The report contains six thematic presentations of analytical commentary covering: World View, People, Environment, Economy, States and Markets, and Global Links.
This study examines the relationship between energy consumption and economic growth for six Central American countries over the period 1980-2004 within a multivariate framework. Given the relatively short span of the time series data, a panel cointegration and error correction model is employed to infer the causal relationship. Based on the heterogeneous panel cointegration test by Pedroni (Pedroni, P., 1999. Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics 61, 653-670; Pedroni, P., 2004. Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis: new results. Econometric Theory 20, 597-627), cointegration is present between real GDP, energy consumption, the labor force, and real gross fixed capital formation with the respective coefficients positive and statistically significant. The Granger-causality results indicate the presence of both short-run and long-run causality from energy consumption to economic growth which supports the growth hypothesis.
We examine properties of residual-based tests for the null of no cointegration for dynamic panels in which both the short-run dynamics and the long-run slope coefficients are permitted to be heterogeneous across individual members of the panel. The tests also allow for individual heterogeneous fixed effects and trend terms, and we consider both pooled within dimension tests and group mean between dimension tests. We derive limiting distributions for these and show that they are normal and free of nuisance parameters. We also provide Monte Carlo evidence to demonstrate their small sample size and power performance, and we illustrate their use in testing purchasing power parity for the post Bretton Woods period.I thank Rich Clarida, Bob Cumby, Mahmoud El-Gamal, Heejoon Kang, Chiwha Kao, Andy Levin, Klaus Neusser, Masao Ogaki, David Papell, Pierre Perron, Abdel Senhadji, Jean-Pierre Urbain, Alan Taylor, and three anonymous referees for helpful comments on various earlier versions of this paper. The paper has also benefited from presentations at the 1994 North American Econometric Society Summer Meetings in Quebec City, the 1994 European Econometric Society Summer Meetings in Maastricht, and workshop seminars at the Board of Governors of the Federal Reserve, INSEE-CREST Paris, IUPUI, Ohio State, Purdue, Queens University Belfast, Rice University University of Houston, and Southern Methodist University. Finally, I thank the following students who provided assistance in the earlier stages of the project: Younghan Kim, Rasmus Ruffer, and Lining Wan.
This article applies recently developed panel unit root and panel cointegration techniques to estimate the long-run and short-run income and price elasticities for residential demand for electricity in G7 countries. The panel results indicate that in the long-run residential demand for electricity is price elastic and income inelastic. The study concludes that from an environmental perspective there is potential to use pricing policies in the G7 countries to curtail residential electricity demand, and thus curb carbon emissions, in the long run.
The recent increase of energy intensity in Spain and the ratification of Kyoto protocol call for the implementation of energy policies in Spain. In this paper, we investigate the relationship between GDP and energy consumption by taking into account several decoupling factors that can affect this linkage. Specifically, we have considered the temporal aggregation of data and its seasonal adjustments, the methodology, the substitution between energy consumption and other inputs, the technological changes and the shifts in both the fuel mix and the composition of the energy outputs. Empirical tests reveals a long run relationships between energy consumption and GDP that can only be established in a complete way with a multivariate cointegration analysis. Furthermore, the Johansen approach reveals a short run unidirectional causality from energy consumption to economic growth. Therefore, primary energy consumption plays an important role as a limiting factor for economic growth in Spain.
Asymptotic distributions and critical values are computed for several residual-based tests of the null of no cointegration in panels for the case of multiple regressors, including regressions with individual-specific fixed effects and time trends. The associated cointegrating vectors and the dynamics of the underlying error processes are permitted considerable heterogeneity across individual members of the panel. Copyright 1999 by Blackwell Publishing Ltd
This paper develops a regression limit theory for nonstationary panel data with large numbers of cross section and time series observations. The limit theory allows for both sequential limits and joins limits, and the relationship between these multidimensional limits is explored. The panel structures considered allow for no time series cointegration, heterogeneous cointegration, homogeneous cointegration, and near-homogeneous cointegration. The paper explores the existence of long-run average relations between integrated panel vectors. In the case of homogeneous and near homogeneous cointegrating panels, a panel fully modified regression estimator is developed and studied.
The relationship between cointegration and error correction models, first suggested by Granger, is here extended and used to develop estimation procedures, tests, and empirical examples. A vector of time series is said to be cointegrated with cointegrating vector a if each element is stationary only after differencing while linear combinations a8xt are themselves stationary. A representation theorem connects the moving average , autoregressive, and error correction representations for cointegrated systems. A simple but asymptotically efficient two-step estimator is proposed and applied. Tests for cointegration are suggested and examined by Monte Carlo simulation. A series of examples are presented. Copyright 1987 by The Econometric Society.
This paper proposes unit root tests for dynamic heterogeneous panels based on the mean of individual unit root statistics. In particular it proposes a standardized t-bar test statistic based on the (augmented) Dickey–Fuller statistics averaged across the groups. Under a general setting this statistic is shown to converge in probability to a standard normal variate sequentially with T (the time series dimension) →∞, followed by N (the cross sectional dimension) →∞. A diagonal convergence result with T and N→∞ while N/T→k,k being a finite non-negative constant, is also conjectured. In the special case where errors in individual Dickey–Fuller (DF) regressions are serially uncorrelated a modified version of the standardized t-bar statistic is shown to be distributed as standard normal as N→∞ for a fixed T, so long as T>5 in the case of DF regressions with intercepts and T>6 in the case of DF regressions with intercepts and linear time trends. An exact fixed N and T test is also developed using the simple average of the DF statistics. Monte Carlo results show that if a large enough lag order is selected for the underlying ADF regressions, then the small sample performances of the t-bar test is reasonably satisfactory and generally better than the test proposed by Levin and Lin (Unpublished manuscript, University of California, San Diego, 1993).
This paper examines whether electoral motives and government ideology influence short-term economic performance. I employ data on annual GDP growth in 21 OECD countries over the 1951-2006 period and provide a battery of empirical tests. In countries with two-party systems GDP growth is boosted before elections and, under leftwing governments, in the first two years of a legislative period. These findings indicate that political cycles are more prevalent in two-party systems because voters can clearly punish or reward political parties for governmental performance. My findings imply that we need more elaborate theories of how government ideology and electoral motives influence short-term economic performance.
The panel data unit root test suggested by Levin and Lin (LL) has been widely used in several applications, notably in papers on tests of the purchasing power parity hypothesis. This test is based on a very restrictive hypothesis which is rarely ever of interest in practice. The Im-Pesaran-Shin (IPS) test relaxes the restrictive assumption of the LL test. This paper argues that although the IPS test has been offered as a generalization of the LL test, it is best viewed as a test for summarizing the evidence from a number of independent tests of the sample hypothesis. This problem has a long statistical history going back to R. A. Fisher. This paper suggests the Fisher test as a panel data unit root test, compares it with the LL and IPS tests, and the Bonferroni bounds test which is valid for correlated tests. Overall, the evidence points to the Fisher test with bootstrap-based critical values as the preferred choice. We also suggest the use of the Fisher test for testing stationarity as the null and also in testing for cointegration in panel data. Copyright 1999 by Blackwell Publishing Ltd
Data: Country Classification
- World Bank
World Bank (2012), "Data: Country Classification", [Online] Available at:
http://data.worldbank.org/about/country-classifications (July, 2012).