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Introduction: Symposium on Energy Sector Convergence
ENEECO-03446; No of Pages 2 Energy Economics xxx (2016) xxx–xxx
Contents lists available at ScienceDirect
Energy Economics journal homepage: www.elsevier.com/locate/eneeco
Introduction: Symposium on Energy Sector Convergence Nicholas Apergis a, Bradley T. Ewing b, James E. Payne c,⁎ a b c
Department of Banking and Financial Management, University of Piraeus, Piraeus, Greece Rawls College of Business, Texas Tech University, Lubbock, TX 79409, United States J. Whitney Bunting College of Business, Georgia College & State University, Milledgeville, GA 31061, United States
a r t i c l e
i n f o
Article history: Received 26 August 2016 Accepted 12 September 2016 Available online xxxx JEL classification: Q4
Convergence is often associated with the economic growth literature as a means to understand disparities in growth patterns and income levels across countries and regions. Drawing from the economic growth literature, various tests of convergence subsequently emerged in the environmental and resource economics literature, as many climate change models and mitigation strategies require an appraisal of the convergence patterns of emissions. Over the past decade, tests of convergence with respect to the energy sector have been more prominent in the energy economics literature. This symposium on Energy Sector Convergence, though by no means exhaustive, provides a flavor of the topics and methodological approaches to encourage further research in this area. Specifically, the symposium addresses three broad areas: convergence in energy intensity (productivity), energy consumption, and energy prices that include studies across countries, regions, and sectors. The first group of studies focuses attention on energy intensity (productivity). In their study entitled “Economy-wide and Manufacturing Energy Productivity Transition Paths and Club Convergence for OECD and Non-OECD Countries”, Steven Parker and Brant Liddle investigate the transition dynamics of energy productivity economy-wide and manufacturing for 33 countries to include 21 low to middle income non-OECD countries over the period 1971 to 2008. Parker and Liddle argue that convergence in energy productivity would imply that specific countries may not need special consideration for global energy/emissions accords to be fair or equitable. Furthermore, their finding that both developing and developed countries are converging towards a common pattern of energy productivity provides evidence of a “leapfrogging process” indicating the need to encourage developing country participation in climate accords. Parker and Liddle begin their analysis in the exami⁎ Corresponding author. E-mail addresses: [email protected] (N. Apergis), [email protected] (B.T. Ewing), [email protected] (J.E. Payne).
nation of sigma and gamma convergence to find that as a group manufacturing energy productivity dynamics are not much different from economy-wide productivity dynamics. Moreover, the OECD and Asian countries yield the greatest energy productivity improvement while Africa and Latin American perform the worst. Next, Parker and Liddle employ the Phillips and Sul (2007) convergence club algorithm which has the advantage of not relying on stationary assumptions and encompasses a variety of possible paths towards convergence. With respect to economy-wide energy productivity Parker and Liddle identify four convergence clubs: (1) China and Mauritius, (2) India, Philippines, Ghana, Colombia, Denmark, United Kingdom, Sweden, and U.S., (3) Indonesia, Tanzania, South Africa, Peru, France, Italy, Japan, and Netherlands, and (4) Malaysia, Thailand, Egypt, Kenya, Morocco, Senegal, Argentina, Bolivia, Brazil, Chile, Costa Rica, Mexico, Spain, and Korea. In terms of manufacturing energy productivity, six convergence clubs emerge: (1) China and Mauritius, (2) India, Malaysia, Costa Rica, Mexico, France, Italy, Japan, Korea, Sweden, and U.S., (3) Thailand, Morocco, South Africa, Colombia, Denmark, United Kingdom, Netherlands, (4) Philippines, Egypt, Ethiopia, Ghana, Kenya, Senegal, Tanzania, Chile, Peru, and Spain, (5) Indonesia and Brazil, and (6) Argentina and Bolivia. The study by Amin Karimu, Runar Brannlund, Tommy Lundgren, and Patrik Soderholm, “Energy Intensity and Convergence in Swedish Industry: A Combined Econometric and Decomposition Analysis”, utilizes a detailed sectoral dataset from 1990 to 2009 to examine the determinants of energy intensity and test for convergence across 14 Swedish industrial sectors within a nonparametric framework. In particular, they isolate two key determinants of changes in energy intensity and convergence patterns: energy efficiency improvements and changes in economic activity. Their findings indicate that energy prices have a significant impact on energy intensity through the efficiency channel more so than the activity channel. Karium, Brannlund, Lundgren, and Soderholm also find that energy intensity convergence across industrial sectors is primarily due to the activity channel. They attribute the results to a shift to less energy-intensive production as a result of energy-intensive manufacturing going abroad. The study by Wesley Burnett and Jessica Madriaga, “The Convergence of U.S. State-Level Energy Intensity”, extends the neoclassical growth model to explore the convergence of energy intensity for U.S. states over the period 1970 to 2013. Within a dynamic panel model framework estimated using generalized method of moments, Burnett and Madariaga find convergence in energy intensity across U.S. states. Moreover, energy use has a small, but positive impact on state level per capita economic growth. The estimated rates of convergence
http://dx.doi.org/10.1016/j.eneco.2016.09.015 0140-9883/© 2016 Elsevier B.V. All rights reserved.
Please cite this article as: Apergis, N., et al., Introduction: Symposium on Energy Sector Convergence, Energy Econ. (2016), http://dx.doi.org/ 10.1016/j.eneco.2016.09.015
2
N. Apergis et al. / Energy Economics xxx (2016) xxx–xxx
suggest that short-run shocks to energy use should not generate any long-run detrimental effects on a state's future economic growth. The second group of studies examines the convergence of energy consumption. Maria Jesus Herrerias, Javier Ordonez, and Carlos Aller in their study, “Residential Energy Consumption: A Convergence Analysis across Chinese Regions”, investigate the effect of urbanization on the long-run patterns of residential energy consumption across Chinese regions over the period 1995 to 2011. Specifically, using Phillips-Sul club convergence, Herrerias, Ordonez, and Aller first examine whether electricity and coal consumption in the rural and urban areas converge to the same long-run equilibrium. Second, their analysis extends to the impact of the regional concentration of economic activity on residential consumption of electricity, coals, and liquid gas. They find that urbanization has led to the use of coal being replaced by electricity in urban residential energy consumption. With respect to the rural areas, the substitution between coal and electricity is unclear, as the results from club convergence reveal that rural and urban residential energy consumption converge to different steady states. In terms of residential energy consumption, they find in the case of coal consumption four clusters of regions with electricity and liquid gas each exhibiting two clusters. Herrerias, Ordonez, and Aller argue that the existence of regional cluster convergence to different equilibrium levels suggests the need for regionally tailored energy policies. In their study, “Stochastic Convergence in Per Capita Fossil Fuel Consumption in U.S. States”, James Payne, Maruska Vizek, and Junsoo Lee apply recently developed LM and RALS-LM unit root tests with endogenously determined structural breaks to test the null hypothesis of a unit root in the log of relative per capita fossil fuel consumption in each of the 50 U.S. states and the District of Columbia over the period 1970 to 2013. Payne, Vizek, and Lee note that the LM and RALS-LM unit root tests offer several advantages over other unit root tests in that they: (1) do not depend on the nuisance parameter and allow for trend breaks under the null hypothesis and (2) utilize information on non-normal errors, unlike nonlinear unit root tests which lose power in the presence of non-normal errors, the RALS-LM unit root tests gain power. With the exception of Nevada, their results reject the null hypothesis of a unit root in the log of relative per capita fossil fuel consumption in support of stochastic convergence. The structural breaks identified were associated in many cases with a number of federal and state policies that were oriented towards lower energy intensity, an increase in energy efficiency, a reduction in carbon emissions, and the expansion of renewable energy, and which may be contributing factors to the finding of convergence in fossil fuel consumption. In a related study to Payne, Vizek, and Lee, Vinod Mishra and Russell Smyth also apply the LM and RALS-LM unit root tests in the paper “Conditional Convergence in Australia's Energy Consumption at the Sector Level”. As noted by Mishra and Smyth, stochastic conditional convergence in energy consumption is relevant in determining whether policies designed to reduce the intensity of energy consumption are effective. The presence of stochastic conditional convergence and growth rates that are modest suggests that such policies designed to reduce energy consumption are effective. Mishra and Smyth use annual data from 1973-74 to 2013-14 for the electricity supply, transport, manufacturing, mining, residential, commercial, and other sectors in Australia. The LM and RALS-LM unit root tests applied to the log of per capita energy consumption in a sector relative to the average energy consumption across sectors reveal stationarity for all seven sectors based on the LM tests and in six of the seven sectors for the RALS-LM tests. The identified structural breaks correspond to shocks in the global energy markets. Hence, Mishra and Smyth find support for stochastic conditional convergence in per capita energy consumption across sectors. The study by Hassan Mohammadi and Rati Ram entitled “Convergence in Energy Consumption Per Capita across U.S. states, 1970-2013: An Exploration through Selected Parametric and Non-Parametric Methods”, employs a battery of convergence tests in their examination of per capita energy consumption across the 48 contiguous U.S. states for the period
1970 to 2013. Their results related to Barro-type regressions indicate a lack of beta convergence and through unit root tests the lack of stochastic convergence. Measures of sigma convergence indicate some degree of divergence supported in part by the flattening of the kernel density estimates. However, the slight decline in the intra-distributional mobility index provides some evidence of gamma convergence. The third group of studies pertains to convergence of energy prices. The study by Nicholas Apergis, Fulvio Fontini, and Julian Inchauspe, “Integration of Regional Electricity Markets in Australia: A Price Convergence Assessment”, utilizes the time varying common factor approach of Phillips-Sul to test both the short-run and long-run wholesale electricity price convergence across Australian electricity markets using weekly wholesale electricity prices from January 1, 1999 to July 31, 2014 (excluding the Northern territory). Specifically, Apergis, Fontini, and Inchauspe differentiate between short-run and longrun price convergence. Given that electricity is a homogenous, nonstorable good delivered through a physically connected network, short-run convergence exists to the extent that transmission capacity allows for arbitrage opportunities whereas long-run price convergence across markets depends on the homogeneity in power supply structures, degree of competitiveness, load levels and profiles, the costs and availability of primary energy sources, and market design and intervention. Their analysis includes the Australian states within the National Electricity Market (NEM) and the South West Interconnected System (SWIS) representing Western Australia in which no interconnection exists. In addition, Apergis, Fontini, and Inchauspe also evaluate the role of a carbon tax introduced from July 2012 to July 2014 in electricity price convergence especially given that the NEM is an energy only market while SWIS is a market with a reserve capacity mechanism. Their findings reveal the absence of short-run price convergence while three price convergence clubs emerge in the long-run: (1) New South Wales, Queensland, and Victoria, (2) Tasmania and Western Australia, and (3) South Australia. By excluding the period of the carbon tax, Apergis, Fontini, and Inchauspe find two convergence clubs: (1) New South Wales, Queensland, Victoria, and South Australia and (2) Tasmania and Western Australia. The study by Seema Narayan and Paresh Narayan, “Estimating the Speed of Adjustment to Target Levels: The Case of Energy Prices”, extends the energy price convergence literature in specifying a partial price adjustment model motivated by the theory of storage in commodity pricing to estimate the speed of adjustment to the optimal price level in a time-varying framework. Using data from the Commodity Research Bureau database, Narayan and Narayan also show that the existence of time-varying bubbles explains, in part, the speed of energy price adjustment. In addition to the role of bubbles in price adjustment, Narayan and Narayan also augment the partial price adjustment model to include several macroeconomic variables. The study by Eric Cardella, Bradley Ewing and Ryan Williams entitled, “Price Volatility and Residential Electricity Decisions: Experimental Evidence on the Convergence of Energy Generating Source”, examines the role of prices and the decision to adopt green energy. Specifically, their paper looks at how the volatility in residential electricity rates impacts consumers' preferences for green power. Their investigation utilizes a choice-based experiment in which survey respondents are presented with various choice scenarios that feature two electricity plans, that is, a conventional plan where electricity is generated by either coal or natural gas and a green plan where electricity is generated renewably from either wind or solar. The monthly price volatility of each plan is systematically varied across the choice scenarios and the results reveal a number of interesting findings with respect to whether or not a household will decide to adopt the green power plan. In particular, increased price volatility in the green plan reduces the likelihood of respondents choosing the green plan while increased volatility in the conventional plan increases the likelihood of choosing the green plan. Interestingly, these price volatility effects hold across different price premiums for the green power plan.
Please cite this article as: Apergis, N., et al., Introduction: Symposium on Energy Sector Convergence, Energy Econ. (2016), http://dx.doi.org/ 10.1016/j.eneco.2016.09.015
Contents lists available at ScienceDirect
Energy Economics journal homepage: www.elsevier.com/locate/eneeco
Introduction: Symposium on Energy Sector Convergence Nicholas Apergis a, Bradley T. Ewing b, James E. Payne c,⁎ a b c
Department of Banking and Financial Management, University of Piraeus, Piraeus, Greece Rawls College of Business, Texas Tech University, Lubbock, TX 79409, United States J. Whitney Bunting College of Business, Georgia College & State University, Milledgeville, GA 31061, United States
a r t i c l e
i n f o
Article history: Received 26 August 2016 Accepted 12 September 2016 Available online xxxx JEL classification: Q4
Convergence is often associated with the economic growth literature as a means to understand disparities in growth patterns and income levels across countries and regions. Drawing from the economic growth literature, various tests of convergence subsequently emerged in the environmental and resource economics literature, as many climate change models and mitigation strategies require an appraisal of the convergence patterns of emissions. Over the past decade, tests of convergence with respect to the energy sector have been more prominent in the energy economics literature. This symposium on Energy Sector Convergence, though by no means exhaustive, provides a flavor of the topics and methodological approaches to encourage further research in this area. Specifically, the symposium addresses three broad areas: convergence in energy intensity (productivity), energy consumption, and energy prices that include studies across countries, regions, and sectors. The first group of studies focuses attention on energy intensity (productivity). In their study entitled “Economy-wide and Manufacturing Energy Productivity Transition Paths and Club Convergence for OECD and Non-OECD Countries”, Steven Parker and Brant Liddle investigate the transition dynamics of energy productivity economy-wide and manufacturing for 33 countries to include 21 low to middle income non-OECD countries over the period 1971 to 2008. Parker and Liddle argue that convergence in energy productivity would imply that specific countries may not need special consideration for global energy/emissions accords to be fair or equitable. Furthermore, their finding that both developing and developed countries are converging towards a common pattern of energy productivity provides evidence of a “leapfrogging process” indicating the need to encourage developing country participation in climate accords. Parker and Liddle begin their analysis in the exami⁎ Corresponding author. E-mail addresses: [email protected] (N. Apergis), [email protected] (B.T. Ewing), [email protected] (J.E. Payne).
nation of sigma and gamma convergence to find that as a group manufacturing energy productivity dynamics are not much different from economy-wide productivity dynamics. Moreover, the OECD and Asian countries yield the greatest energy productivity improvement while Africa and Latin American perform the worst. Next, Parker and Liddle employ the Phillips and Sul (2007) convergence club algorithm which has the advantage of not relying on stationary assumptions and encompasses a variety of possible paths towards convergence. With respect to economy-wide energy productivity Parker and Liddle identify four convergence clubs: (1) China and Mauritius, (2) India, Philippines, Ghana, Colombia, Denmark, United Kingdom, Sweden, and U.S., (3) Indonesia, Tanzania, South Africa, Peru, France, Italy, Japan, and Netherlands, and (4) Malaysia, Thailand, Egypt, Kenya, Morocco, Senegal, Argentina, Bolivia, Brazil, Chile, Costa Rica, Mexico, Spain, and Korea. In terms of manufacturing energy productivity, six convergence clubs emerge: (1) China and Mauritius, (2) India, Malaysia, Costa Rica, Mexico, France, Italy, Japan, Korea, Sweden, and U.S., (3) Thailand, Morocco, South Africa, Colombia, Denmark, United Kingdom, Netherlands, (4) Philippines, Egypt, Ethiopia, Ghana, Kenya, Senegal, Tanzania, Chile, Peru, and Spain, (5) Indonesia and Brazil, and (6) Argentina and Bolivia. The study by Amin Karimu, Runar Brannlund, Tommy Lundgren, and Patrik Soderholm, “Energy Intensity and Convergence in Swedish Industry: A Combined Econometric and Decomposition Analysis”, utilizes a detailed sectoral dataset from 1990 to 2009 to examine the determinants of energy intensity and test for convergence across 14 Swedish industrial sectors within a nonparametric framework. In particular, they isolate two key determinants of changes in energy intensity and convergence patterns: energy efficiency improvements and changes in economic activity. Their findings indicate that energy prices have a significant impact on energy intensity through the efficiency channel more so than the activity channel. Karium, Brannlund, Lundgren, and Soderholm also find that energy intensity convergence across industrial sectors is primarily due to the activity channel. They attribute the results to a shift to less energy-intensive production as a result of energy-intensive manufacturing going abroad. The study by Wesley Burnett and Jessica Madriaga, “The Convergence of U.S. State-Level Energy Intensity”, extends the neoclassical growth model to explore the convergence of energy intensity for U.S. states over the period 1970 to 2013. Within a dynamic panel model framework estimated using generalized method of moments, Burnett and Madariaga find convergence in energy intensity across U.S. states. Moreover, energy use has a small, but positive impact on state level per capita economic growth. The estimated rates of convergence
http://dx.doi.org/10.1016/j.eneco.2016.09.015 0140-9883/© 2016 Elsevier B.V. All rights reserved.
Please cite this article as: Apergis, N., et al., Introduction: Symposium on Energy Sector Convergence, Energy Econ. (2016), http://dx.doi.org/ 10.1016/j.eneco.2016.09.015
2
N. Apergis et al. / Energy Economics xxx (2016) xxx–xxx
suggest that short-run shocks to energy use should not generate any long-run detrimental effects on a state's future economic growth. The second group of studies examines the convergence of energy consumption. Maria Jesus Herrerias, Javier Ordonez, and Carlos Aller in their study, “Residential Energy Consumption: A Convergence Analysis across Chinese Regions”, investigate the effect of urbanization on the long-run patterns of residential energy consumption across Chinese regions over the period 1995 to 2011. Specifically, using Phillips-Sul club convergence, Herrerias, Ordonez, and Aller first examine whether electricity and coal consumption in the rural and urban areas converge to the same long-run equilibrium. Second, their analysis extends to the impact of the regional concentration of economic activity on residential consumption of electricity, coals, and liquid gas. They find that urbanization has led to the use of coal being replaced by electricity in urban residential energy consumption. With respect to the rural areas, the substitution between coal and electricity is unclear, as the results from club convergence reveal that rural and urban residential energy consumption converge to different steady states. In terms of residential energy consumption, they find in the case of coal consumption four clusters of regions with electricity and liquid gas each exhibiting two clusters. Herrerias, Ordonez, and Aller argue that the existence of regional cluster convergence to different equilibrium levels suggests the need for regionally tailored energy policies. In their study, “Stochastic Convergence in Per Capita Fossil Fuel Consumption in U.S. States”, James Payne, Maruska Vizek, and Junsoo Lee apply recently developed LM and RALS-LM unit root tests with endogenously determined structural breaks to test the null hypothesis of a unit root in the log of relative per capita fossil fuel consumption in each of the 50 U.S. states and the District of Columbia over the period 1970 to 2013. Payne, Vizek, and Lee note that the LM and RALS-LM unit root tests offer several advantages over other unit root tests in that they: (1) do not depend on the nuisance parameter and allow for trend breaks under the null hypothesis and (2) utilize information on non-normal errors, unlike nonlinear unit root tests which lose power in the presence of non-normal errors, the RALS-LM unit root tests gain power. With the exception of Nevada, their results reject the null hypothesis of a unit root in the log of relative per capita fossil fuel consumption in support of stochastic convergence. The structural breaks identified were associated in many cases with a number of federal and state policies that were oriented towards lower energy intensity, an increase in energy efficiency, a reduction in carbon emissions, and the expansion of renewable energy, and which may be contributing factors to the finding of convergence in fossil fuel consumption. In a related study to Payne, Vizek, and Lee, Vinod Mishra and Russell Smyth also apply the LM and RALS-LM unit root tests in the paper “Conditional Convergence in Australia's Energy Consumption at the Sector Level”. As noted by Mishra and Smyth, stochastic conditional convergence in energy consumption is relevant in determining whether policies designed to reduce the intensity of energy consumption are effective. The presence of stochastic conditional convergence and growth rates that are modest suggests that such policies designed to reduce energy consumption are effective. Mishra and Smyth use annual data from 1973-74 to 2013-14 for the electricity supply, transport, manufacturing, mining, residential, commercial, and other sectors in Australia. The LM and RALS-LM unit root tests applied to the log of per capita energy consumption in a sector relative to the average energy consumption across sectors reveal stationarity for all seven sectors based on the LM tests and in six of the seven sectors for the RALS-LM tests. The identified structural breaks correspond to shocks in the global energy markets. Hence, Mishra and Smyth find support for stochastic conditional convergence in per capita energy consumption across sectors. The study by Hassan Mohammadi and Rati Ram entitled “Convergence in Energy Consumption Per Capita across U.S. states, 1970-2013: An Exploration through Selected Parametric and Non-Parametric Methods”, employs a battery of convergence tests in their examination of per capita energy consumption across the 48 contiguous U.S. states for the period
1970 to 2013. Their results related to Barro-type regressions indicate a lack of beta convergence and through unit root tests the lack of stochastic convergence. Measures of sigma convergence indicate some degree of divergence supported in part by the flattening of the kernel density estimates. However, the slight decline in the intra-distributional mobility index provides some evidence of gamma convergence. The third group of studies pertains to convergence of energy prices. The study by Nicholas Apergis, Fulvio Fontini, and Julian Inchauspe, “Integration of Regional Electricity Markets in Australia: A Price Convergence Assessment”, utilizes the time varying common factor approach of Phillips-Sul to test both the short-run and long-run wholesale electricity price convergence across Australian electricity markets using weekly wholesale electricity prices from January 1, 1999 to July 31, 2014 (excluding the Northern territory). Specifically, Apergis, Fontini, and Inchauspe differentiate between short-run and longrun price convergence. Given that electricity is a homogenous, nonstorable good delivered through a physically connected network, short-run convergence exists to the extent that transmission capacity allows for arbitrage opportunities whereas long-run price convergence across markets depends on the homogeneity in power supply structures, degree of competitiveness, load levels and profiles, the costs and availability of primary energy sources, and market design and intervention. Their analysis includes the Australian states within the National Electricity Market (NEM) and the South West Interconnected System (SWIS) representing Western Australia in which no interconnection exists. In addition, Apergis, Fontini, and Inchauspe also evaluate the role of a carbon tax introduced from July 2012 to July 2014 in electricity price convergence especially given that the NEM is an energy only market while SWIS is a market with a reserve capacity mechanism. Their findings reveal the absence of short-run price convergence while three price convergence clubs emerge in the long-run: (1) New South Wales, Queensland, and Victoria, (2) Tasmania and Western Australia, and (3) South Australia. By excluding the period of the carbon tax, Apergis, Fontini, and Inchauspe find two convergence clubs: (1) New South Wales, Queensland, Victoria, and South Australia and (2) Tasmania and Western Australia. The study by Seema Narayan and Paresh Narayan, “Estimating the Speed of Adjustment to Target Levels: The Case of Energy Prices”, extends the energy price convergence literature in specifying a partial price adjustment model motivated by the theory of storage in commodity pricing to estimate the speed of adjustment to the optimal price level in a time-varying framework. Using data from the Commodity Research Bureau database, Narayan and Narayan also show that the existence of time-varying bubbles explains, in part, the speed of energy price adjustment. In addition to the role of bubbles in price adjustment, Narayan and Narayan also augment the partial price adjustment model to include several macroeconomic variables. The study by Eric Cardella, Bradley Ewing and Ryan Williams entitled, “Price Volatility and Residential Electricity Decisions: Experimental Evidence on the Convergence of Energy Generating Source”, examines the role of prices and the decision to adopt green energy. Specifically, their paper looks at how the volatility in residential electricity rates impacts consumers' preferences for green power. Their investigation utilizes a choice-based experiment in which survey respondents are presented with various choice scenarios that feature two electricity plans, that is, a conventional plan where electricity is generated by either coal or natural gas and a green plan where electricity is generated renewably from either wind or solar. The monthly price volatility of each plan is systematically varied across the choice scenarios and the results reveal a number of interesting findings with respect to whether or not a household will decide to adopt the green power plan. In particular, increased price volatility in the green plan reduces the likelihood of respondents choosing the green plan while increased volatility in the conventional plan increases the likelihood of choosing the green plan. Interestingly, these price volatility effects hold across different price premiums for the green power plan.
Please cite this article as: Apergis, N., et al., Introduction: Symposium on Energy Sector Convergence, Energy Econ. (2016), http://dx.doi.org/ 10.1016/j.eneco.2016.09.015