I am, like almost 1200 other participants, at the WCERE in Istanbul. Yesterday there was an interesting panel session on climate change with Jeffrey Sachs, Ottmar Edenhofer (who is apparently meeting the Pope today), Marianne Fay from the World Bank, Laurence Tubiana - the new French climate change ambassador - and Carlo Carraro as chair. All the participants agreed that the new framework for climate change policy that will be established at Paris next year must make a break from previous agreements and pledges in consisting primarily of designing long-term transformation pathways rather than primarily short-term targets. Obviously, short-term steps will still be needed. The thinking behind this was best expressed by Marianne Fay. She showed a slide with a picture of the Freedom Tower in New York and a small cottage side by side. She asked: "If you wanted to build this tower, would the house on the left be a reasonable first step?" Similarly, we could ask whether shifting to natural gas is a reasonable first step to decarbonizing the economy. A long-term perspective is needed. Jeffrey Sachs made a point that spot carbon markets aren't an appropriate tool for long-term climate policy. The short-term price keeps fluctuating and there is no long-term futures market. Instead a predictably rising carbon tax is needed. Technology policies are also needed to complement the carbon price. The consensus is that this is where we should head.
David Stern's Blog on Energy, the Environment, Economics, and the Science of Science
Monday, June 30, 2014
World Congress of Environmental and Resource Economics
I am, like almost 1200 other participants, at the WCERE in Istanbul. Yesterday there was an interesting panel session on climate change with Jeffrey Sachs, Ottmar Edenhofer (who is apparently meeting the Pope today), Marianne Fay from the World Bank, Laurence Tubiana - the new French climate change ambassador - and Carlo Carraro as chair. All the participants agreed that the new framework for climate change policy that will be established at Paris next year must make a break from previous agreements and pledges in consisting primarily of designing long-term transformation pathways rather than primarily short-term targets. Obviously, short-term steps will still be needed. The thinking behind this was best expressed by Marianne Fay. She showed a slide with a picture of the Freedom Tower in New York and a small cottage side by side. She asked: "If you wanted to build this tower, would the house on the left be a reasonable first step?" Similarly, we could ask whether shifting to natural gas is a reasonable first step to decarbonizing the economy. A long-term perspective is needed. Jeffrey Sachs made a point that spot carbon markets aren't an appropriate tool for long-term climate policy. The short-term price keeps fluctuating and there is no long-term futures market. Instead a predictably rising carbon tax is needed. Technology policies are also needed to complement the carbon price. The consensus is that this is where we should head.
Thursday, June 26, 2014
Canberra is the Best Place to Live in the World According to the OECD
Australia is the best country and the ACT is the best region in Australia. I checked the OECD website, and giving equal weight to each of the criteria the OECD ranks, the ACT is the highest scoring region in the world. Of course, that is not how most Australians see it. I met an Australian woman at JFK airport last week while waiting to take the train and she asked me where I lived. When I answered: "Canberra", she said: "Why would you do that to yourself?"
Wednesday, June 25, 2014
Follow Up on "Energy and Economic Growth: The Stylized Facts" at Econbrowser
James Hamilton has a new post on Econbrowser based partly on our paper Energy and Economic Growth: The Stylized Facts which I recently presented at the IAEE meeting in New York. I'd add that oil use has been flat in recent years but that was compensated for by increases in the use of natural gas, coal, and renewables. So, recent data don't substantially deviate from our stylized fact.
Today, I arrived at A Toxa, an island in Galicia, in the northwest of Spain. It is really beautiful here. Tomorrow the 6th Atlantic Workshop on Energy and Environmental Economics
starts here. I am giving a presentation in the final session tomorrow on our paper on modeling the emissions-income relationship using long-run growth rates.
Today, I arrived at A Toxa, an island in Galicia, in the northwest of Spain. It is really beautiful here. Tomorrow the 6th Atlantic Workshop on Energy and Environmental Economics
starts here. I am giving a presentation in the final session tomorrow on our paper on modeling the emissions-income relationship using long-run growth rates.
Thursday, June 19, 2014
High-Ranked Social Science Journal Articles Can Be Identified from Early Citation Information
I have posted a new bibliometric working paper , which investigates how well we can predict future cumulative citations from the first citations received by a paper in the disciplines of economics and political science.
It is usually assumed that citations accumulate too slowly in social sciences apart from psychology to be useful for short-term research assessment. For this reason, the Australian Government’s Excellence in Research for Australia (ERA) exercise, which attempts to assess the research quality of universities in the previous 5 years, uses peer review in social science disciplines apart from psychology for this reason but uses citation analysis for psychology and all natural sciences. This peer review process seems to me to be a wasteful duplication of effort to review research outputs that have already passed through a peer review process once.
I show that, surprisingly, citations received by journal articles in the social sciences in the first one to two years after publication are strongly predictive for citations received in future years. By contrast, I show that journal impact factors are mostly useful in the year of publication and their contribution to predicting citations declines rapidly thereafter.
If it is actually possible to predict citations fairly reliably in social science disciplines, then it should also be easy to predict them in the natural sciences. This means that it should be possible to expand bibliometric analysis in research evaluation exercises to all disciplines apart from the humanities and arts. It also means that we should pay attention to the early citations received by papers when we evaluate individual academics for hiring and promotion. Impact factors are reflective of journal selectivity, which we frequently do not have easily available data on. But they only explain about 16-17% of the variation in rankings of papers six years later conditional on the citations already received in the year of publication. The latter explain 13-14% of the variation. But at the end of the year following publication, accumulated citations explain 52-53% of the variation in cumulative citations after 6 years and 73% at the end of the second year after publication.
These models could be improved by adding information on the characteristics of the articles themselves and their authors, but that was much too time consuming to do for the almost 12,000 articles in my sample.
I have submitted a copy of my paper to the HEFCE inquiry on the use of metrics in research assessment.
It is usually assumed that citations accumulate too slowly in social sciences apart from psychology to be useful for short-term research assessment. For this reason, the Australian Government’s Excellence in Research for Australia (ERA) exercise, which attempts to assess the research quality of universities in the previous 5 years, uses peer review in social science disciplines apart from psychology for this reason but uses citation analysis for psychology and all natural sciences. This peer review process seems to me to be a wasteful duplication of effort to review research outputs that have already passed through a peer review process once.
I show that, surprisingly, citations received by journal articles in the social sciences in the first one to two years after publication are strongly predictive for citations received in future years. By contrast, I show that journal impact factors are mostly useful in the year of publication and their contribution to predicting citations declines rapidly thereafter.
If it is actually possible to predict citations fairly reliably in social science disciplines, then it should also be easy to predict them in the natural sciences. This means that it should be possible to expand bibliometric analysis in research evaluation exercises to all disciplines apart from the humanities and arts. It also means that we should pay attention to the early citations received by papers when we evaluate individual academics for hiring and promotion. Impact factors are reflective of journal selectivity, which we frequently do not have easily available data on. But they only explain about 16-17% of the variation in rankings of papers six years later conditional on the citations already received in the year of publication. The latter explain 13-14% of the variation. But at the end of the year following publication, accumulated citations explain 52-53% of the variation in cumulative citations after 6 years and 73% at the end of the second year after publication.
These models could be improved by adding information on the characteristics of the articles themselves and their authors, but that was much too time consuming to do for the almost 12,000 articles in my sample.
I have submitted a copy of my paper to the HEFCE inquiry on the use of metrics in research assessment.
Energy and Economic Growth: The Animated GIF
It seems that everyone loves the animation of energy use per capita and GDP per capita that I am showing as part of my presentations on Energy and Economic Growth: The Stylized Facts. So, at James Hamilton's suggestion and with Zsuzsanna's help I have made an animated GIF of this slide sequence:
The graph is for the 99 countries that have data in both the Penn World Table (7.0) and the IEA Energy Balances. The line is the best fit log-log regression computed by Excel. As you can see the relationship between these two variables has been very stable over the last forty years globally.
The graph is for the 99 countries that have data in both the Penn World Table (7.0) and the IEA Energy Balances. The line is the best fit log-log regression computed by Excel. As you can see the relationship between these two variables has been very stable over the last forty years globally.
Wednesday, June 18, 2014
World Energy Use Increased 2.3% in 2013
The annual BP Statistical Review was just released. It shows that world energy use increased by 2.3% in 2013. According to the IMF, the world economy grew 3% in 2013. World population is growing at about 1.1% p.a. Therefore, there was a 1.2% increase in per capita energy use for a 1.9% increase in GDP per capita - a ratio of 0.63 - which is a little below our stylized fact that energy use tends to increase by 0.7% for a 1% increase in GDP.
Tuesday, June 17, 2014
Environment and Development Economics is 20 Years Old
And there is a special issue to celebrate. You can find the introductory article from the editors here. One of my tasks as a post-doc at University of York was helping my boss, Charles Perrings, with the administrative tasks for the new journal like sending invitation letters to the editorial board members. It's also 20 years since I got my PhD - my defence was in April 1994 - I started the post-doc at York as an "ABD" in September 1993. Time flies!
Right now I'm at the IAEE meeting in New York City, will be going on to the Atlantic Workshop in Spain next week and the World Congresss of Environmental and Resource Economics in Istanbul the following week. Not surprisingly, the main talk here is about shale oil and gas and their implications. Flying over Pennsylvania on Sunday I saw quite a few drilling sites...
Right now I'm at the IAEE meeting in New York City, will be going on to the Atlantic Workshop in Spain next week and the World Congresss of Environmental and Resource Economics in Istanbul the following week. Not surprisingly, the main talk here is about shale oil and gas and their implications. Flying over Pennsylvania on Sunday I saw quite a few drilling sites...
Saturday, June 7, 2014
Friday, June 6, 2014
The Environmental Kuznets Curve: A Primer
I've updated my article on the environmental Kuznets curve that appeared in the Encyclopedia of Energy in 2004. The revised version will be available as part of Elsevier's
Online Reference Database: Earth Systems and Environmental Sciences. I've also posted a working paper version of the article titled: The Environmental Kuznets Curve: A Primer. Despite all the papers that have been published on the topic in the past ten years, I don't think my main messages have changed much. Increases in income tend to increase emissions per capita but time related and other effects can reduce emissions. On the other hand concentrations of some local pollutants are reduced by income increases. The section on theory is a bit more optimistic than I was in 2004 but I think there is still opportunity to develop a comprehensive theory of how income and emissions evolve. I also write in the conclusions that recently developed econometric methods have also only been applied to analyze a couple of well-known pollutants. Therefore, I expect that in coming years this will continue to be an active area of research interest. The emerging issue of how emissions evolve over the business cycle is also likely to be an area of expanding research.
Thursday, June 5, 2014
Energy and Economic Growth: The Stylized Facts
I contributed an article to the IAEE Energy Forum as part of their report on the New York City conference of IAEE. The topic of our paper that I will present in New York on 16th June is "Energy and Economic Growth: The Stylized Facts". The full paper is available as part of the conference proceedings. This has been a project under development for a while, being the subject of my "foundation seminar" (=inaugural lecture) here at Crawford School. Things progressed further once Zsuzsanna Cserekylei put a consistent dataset together for the 1971-2010 period and did the analysis. Then Mar Rubio contributed historical data and analysis. Anyway, this is the text of our article:
What overall patterns, or stylized facts, characterize the relationship between economic growth and energy use both across countries and over time? Energy economists and economic historians have investigated these issues, but existing research has either looked at how energy use and economic development vary across countries at one point in time or how they evolve over time in individual countries or groups of countries. Researchers have not linked together the cross-sectional and time series behaviors despite their obvious dependence on each other.
We investigate the links between the time and cross-sectional (or income per capita) dimensions using two datasets. One is a dataset for 99 countries from 1971 to 2010 that uses IEA and Penn World Table data. The other comprises historical data for the U.S. and a number of European and Latin American countries that extends back to 1800 for the U.S. and some Northern European countries and to later dates in the 19th and early 20th century for the other countries.
In recent years, economic historians, including one of the authors of this paper, Mar Rubio, have been working to reconstruct the energy history of many countries in Europe and the Americas for the years before the Second World War. Some of the historical data we use was prepared for the recently published Power to the People, authored by Astrid Kander, Paolo Malanima, and Paul Warde and published by Princeton University Press. Mar Rubio collaborated with Kander et al. on the Spanish data for that volume and led a team that developed historical data for Latin America. Though these data are obviously much more uncertain than those for recent years, they can provide insights into the long-run relationship between energy and economic development.
Our key finding from the recent data is that there has been a fairly stable relationship between countries’ GDP per capita measured in purchasing power parity adjusted Dollars and their per capita energy use over the last 40 years. A 1% increase in income per capita across countries is associated with a 0.7% increase in per capita energy use. This implies that energy intensity (energy use/GDP) is lower in richer countries and that on average a 1% increase in income per capita is associated with a 0.3% decrease in energy intensity.
The relationship is also stable in the sense that the average energy use per capita associated with any given level of income per capita has not changed over the four decades. This means that the typical country only managed to reduce its energy intensity by increasing its income per capita. A different way of looking at the same data is to compare countries’ average GDP per capita growth rate from 1971 to 2010 to the rate of change in their energy intensity over the same period. This relationship is shown in Figure 1:
The graph shows that higher rates of economic growth are associated with higher rates of decline in energy intensity. The graph also shows that if a country’s economic growth was zero then not only did its energy intensity not decline, but actually it increased on average.
Figure 1 also indicates that there are many countries where energy intensity rose despite economic growth. Our second main finding is that there was convergence in energy intensity over time and that the countries whose energy intensity rose typically had low energy intensity at the beginning of the period. Countries that were very energy intensive typically saw declines in energy intensity. There is now a tighter relationship between income and energy use than there was forty years ago.
In other words, though there has been some degree of “decoupling” of energy and growth in some formerly energy intensive economies, this has not been the common experience. Rather, there has been a homogenization, with countries increasingly resembling each other, while energy intensity globally has declined, but not by enough to reduce energy use.
This picture is borne out in the historical data too. Figure 2 shows the evolution of energy intensity and income over the last two centuries for four representative countries. Energy intensity appears to have declined the most in the United States, which was the most energy intensive economy in the 19th Century. On the other hand, energy intensity has been fairly stable in Spain, which was a very low energy intensity economy in the 19th Century. These time-paths are superimposed on the global distribution of energy intensity and income in 2010. This shows that in the past the United States was more energy intensive for its income level than any countries are today but that in the last few decades it has ceased to be remarkable in that way. On the other hand, the time paths of Sweden, Brazil, and Spain are mostly within the present day energy intensity distribution.
Our paper in the online proceedings also covers other regularities in the data. Specifically, there is some evidence that the share of energy in costs declines over time. But this “stylized fact” is still more of a prediction than a proven regularity. As is well known, the quality of energy increases over time and with income as countries have transitioned from traditional biomass, to fossil fuels, to primary electricity over time. We also find that the energy/capital ratio, which is an alternative to energy intensity as an indicator of overall energy efficiency, behaves somewhat similarly to energy intensity.
Future theoretical models of the relationship between energy use and economic development will need to take these stylized facts into account and make sure that their predictions match the facts. The stylized facts might also be useful for developing simple business as usual energy use scenarios.
What overall patterns, or stylized facts, characterize the relationship between economic growth and energy use both across countries and over time? Energy economists and economic historians have investigated these issues, but existing research has either looked at how energy use and economic development vary across countries at one point in time or how they evolve over time in individual countries or groups of countries. Researchers have not linked together the cross-sectional and time series behaviors despite their obvious dependence on each other.
We investigate the links between the time and cross-sectional (or income per capita) dimensions using two datasets. One is a dataset for 99 countries from 1971 to 2010 that uses IEA and Penn World Table data. The other comprises historical data for the U.S. and a number of European and Latin American countries that extends back to 1800 for the U.S. and some Northern European countries and to later dates in the 19th and early 20th century for the other countries.
In recent years, economic historians, including one of the authors of this paper, Mar Rubio, have been working to reconstruct the energy history of many countries in Europe and the Americas for the years before the Second World War. Some of the historical data we use was prepared for the recently published Power to the People, authored by Astrid Kander, Paolo Malanima, and Paul Warde and published by Princeton University Press. Mar Rubio collaborated with Kander et al. on the Spanish data for that volume and led a team that developed historical data for Latin America. Though these data are obviously much more uncertain than those for recent years, they can provide insights into the long-run relationship between energy and economic development.
Our key finding from the recent data is that there has been a fairly stable relationship between countries’ GDP per capita measured in purchasing power parity adjusted Dollars and their per capita energy use over the last 40 years. A 1% increase in income per capita across countries is associated with a 0.7% increase in per capita energy use. This implies that energy intensity (energy use/GDP) is lower in richer countries and that on average a 1% increase in income per capita is associated with a 0.3% decrease in energy intensity.
The relationship is also stable in the sense that the average energy use per capita associated with any given level of income per capita has not changed over the four decades. This means that the typical country only managed to reduce its energy intensity by increasing its income per capita. A different way of looking at the same data is to compare countries’ average GDP per capita growth rate from 1971 to 2010 to the rate of change in their energy intensity over the same period. This relationship is shown in Figure 1:
The graph shows that higher rates of economic growth are associated with higher rates of decline in energy intensity. The graph also shows that if a country’s economic growth was zero then not only did its energy intensity not decline, but actually it increased on average.
Figure 1 also indicates that there are many countries where energy intensity rose despite economic growth. Our second main finding is that there was convergence in energy intensity over time and that the countries whose energy intensity rose typically had low energy intensity at the beginning of the period. Countries that were very energy intensive typically saw declines in energy intensity. There is now a tighter relationship between income and energy use than there was forty years ago.
In other words, though there has been some degree of “decoupling” of energy and growth in some formerly energy intensive economies, this has not been the common experience. Rather, there has been a homogenization, with countries increasingly resembling each other, while energy intensity globally has declined, but not by enough to reduce energy use.
This picture is borne out in the historical data too. Figure 2 shows the evolution of energy intensity and income over the last two centuries for four representative countries. Energy intensity appears to have declined the most in the United States, which was the most energy intensive economy in the 19th Century. On the other hand, energy intensity has been fairly stable in Spain, which was a very low energy intensity economy in the 19th Century. These time-paths are superimposed on the global distribution of energy intensity and income in 2010. This shows that in the past the United States was more energy intensive for its income level than any countries are today but that in the last few decades it has ceased to be remarkable in that way. On the other hand, the time paths of Sweden, Brazil, and Spain are mostly within the present day energy intensity distribution.
Our paper in the online proceedings also covers other regularities in the data. Specifically, there is some evidence that the share of energy in costs declines over time. But this “stylized fact” is still more of a prediction than a proven regularity. As is well known, the quality of energy increases over time and with income as countries have transitioned from traditional biomass, to fossil fuels, to primary electricity over time. We also find that the energy/capital ratio, which is an alternative to energy intensity as an indicator of overall energy efficiency, behaves somewhat similarly to energy intensity.
Future theoretical models of the relationship between energy use and economic development will need to take these stylized facts into account and make sure that their predictions match the facts. The stylized facts might also be useful for developing simple business as usual energy use scenarios.
Asia and the Pacific Policy Society
The Asia and the Pacific Policy Society is an academic society set up in association with Crawford School's flagship journal, Asia and the Pacific Policy Studies. Joining the society is free.
Sunday, June 1, 2014
First Issue of JAERE is Out
The first issue of the new Journal of the Association of Environmental and Resource Economics has now been published. A mix of different topics and some big names, though not as many as one might expect for the first issue of a new journal.
The Relationship Between per Capita Energy Use and Income per Capita Has Been Very Stable
First preview of the paper that I will be presenting at the IAEE meeting in New York in a couple of weeks. Using Penn World Table 7 data for GDP per capita and IEA data for energy use, we (me, Zsuzsanna Csereklyei and Mar Rubio) found that the relationship between energy use per capita and income per capita has been very stable from 1971 to 2010 for a group of 99 countries. I've prepared an animation that shows this relationship. Just click through the pages in the pdf to see what happens as countries have grown (or not) over time.