Wednesday, May 6, 2015

Research Assessment Using Early Citation Information

A new paper with Stephan Bruns on carrying out research assessment like the UK REF and the Australian ERA using citations data rather than peer review. We did a lot of the work of processing the data (doing fancy things with R and manually checking names of universities in Excel) when I visited Stephan in Kassel in November.

The problem with research assessment as carried out in Britain and in the social sciences in Australia is that publications that have already passed through a peer review process are again peer reviewed by the assessment panels. This involves a significant workload for many academics who are supposed to read these papers as well as the effort a each university put into selecting the publications that will be reviewed. However, this second peer review though is inferior to the first. If instead citation based metrics were used the whole process could be done much faster and cheaper. In Australia the natural sciences and psychology are assessed using citation analysis. I think this can be extended to at least some other social sciences including economics.

UK REF panels can also put some weight on citations data in some disciplines including most natural sciences and economics, but only as a positive indicator of academic significance and in very much a secondary role to peer review. This represents a change from the previous RAE, which prohibited the use of citations data by panels. This paper provides additional evidence on the potential effectiveness of citation analysis as a method of research assessment. We hope our results can inform the future development of assessment exercises such as the REF and ERA.

One reason why citations analysis is less accepted in the social sciences than in the natural sciences is the belief that citations accumulate too slowly in most social sciences such as economics to be useful for short-term research assessmen.

My 2014 paper in PLoS ONE shows that long-run citations to articles in economics and political science are fairly predictable from the first few years of citations to those articles. However, research assessment evaluates universities rather than single articles. In this new paper, we show that rank correlations are greatly increased when we aggregate over the economics publications of a university and also when we aggregate publications over time. The rank correlation for UK universities for citations received till the end of 2004 (2005) by economics articles published in 2003 and 2004 with total citations to those articles received through 2014 is 0.91 (0.97). These are high correlations. Correlations for Australia are a bit lower.

Our results here show that at the department or university level citations definitely accumulate fast enough in economics in order to be able to predict longer run citation outcomes of recent publications. It's not true that citations accumulate too slowly in the social sciences to be used in research assessment.

On the other hand, the rank correlation between our early citations indicators and the outcome of research assessment exercises in the UK and Australia ranges from 0.67-0.76. These results suggest that citation analysis is useful for research assessment in economics if the assessor is willing to use cumulative citations as a measure of research strength, though there do appear to be some systematic differences between peer-review based research assessment and our citation analysis, especially in the UK. Part of the difference will emerge due to the differences between the sample of publications we selected to assess and the publications actually selected in the 2010 ERA and 2008 RAE.

Friday, April 24, 2015

Carbon dioxide emissions in the short run: The rate and sources of economic growth matter

Another paper in our ""trends and drivers" series that emerged from my IPCC work. We already released a paper on total greenhouse gas emissions in the long run that I coauthored with Luis Sanchez and a more methodological paper with Reyer Gerlagh, Paul Burke, and Zeba Anjum on fossil fuel CO2 and SO2 emissions in the long run.

The new paper coauthored with Paul Burke and Md. Shahiduzzaman focuses on what happens to fossil fuel carbon dioxide emissions over the business cycle time frame. This topic has received a bit of attention recently. We looked at the issue of what happened after the 2008-9 "Great Recession" in a short 2012 paper in Nature Climate Change that followed up on a paper by Glen Peters and others. Emissions grew very strongly in the recovery in 2010. Our new research shows that 2010 was an unusual year and usually emissions do not rise strongly in the recovery from a recession. In another 2012 paper in Nature Climate Change,, Richard York reported that the response of emissions to expansions and recessions is asymmetric. When the economy is growing the elasticity of emissions with respect to GDP is greater than when it is declining. Our paper tests York’s results and finds that asymmetry is only statistically significant when expansions and recessions of several years in length are considered.

That Gross World Product and CO2 emissions growth rates are tightly linked can be easily seen in the following graph. But there are many details to the story. For example, using country-level data we find that lagged effects are important: around 40% of the effect of economic growth on emissions isn’t realized until a subsequent year.

Some of the paper’s results are summarized in the graph below. We find that the average same-year emissions-income elasticity is about 0.5, but that this elasticity varies depending on the source of economic growth. Agricultural growth has relatively small emissions effects, whereas industrial growth is relatively emissions intensive. External shocks from export markets have quite large domestic emissions implications, presumably because they mostly affect industrial output.

Full abstract: This paper investigates the short-run effects of economic growth on carbon dioxide emissions from the combustion of fossil fuels and the manufacture of cement for 189 countries over the period 1961–2010. Contrary to what has previously been reported, we conclude that there is no strong evidence that the emissions-income elasticity is larger during individual years of economic expansion as compared to recession. Significant evidence of asymmetry emerges when effects over longer periods are considered. We find that economic growth tends to increase emissions not only in the same year, but also in subsequent years. Delayed effects – especially noticeable in the road transport sector – mean that emissions tend to grow more quickly after booms and more slowly after recessions. Emissions are more sensitive to fluctuations in industrial value-added than agricultural value-added, with services being an intermediate case. On the expenditure side, growth in consumption and in investment have similar implications for national emissions. External shocks have a relatively large emissions impact, and the short-run emissions-income elasticity does not appear to decline as incomes increase. Economic growth and emissions have been more tightly linked in fossil-fuel rich countries.

P.S. 4 May 2015
The paper was accepted for publication in Global Environmental Change. Yeah, we posted the working paper when we resubmitted the paper to the journal. Still, overall that was a very fast publication experience with the first journal we submitted to (on 18 December 2014) accepting the paper. This isn't always the case :)

Saturday, March 28, 2015

Drivers of Industrial and Non-Industrial Greenhouse Gas Emissions

Another new working paper this time coauthored with my masters student Luis Sanchez. We use the new approach to modeling the income-emissions relationship pioneered by Anjum et al but using total greenhouse gas emission rather than just CO2 emissions from fossil fuel combustion and cement production. This is closer to the discussion I wrote in Chapter 5 of the Working Group III IPCC Report. Anjum et al. used the more limited emissions variable because the IPCC wouldn't allow us to use the data assembled for the report in other research and it took a lot of effort on Luis' part to put the data together from the raw Edgar data. Also, economists are more familiar with the narrow industrial CO2 emissions variable and so we thought we'd do an analysis of that first.

There has been extensive analysis of the drivers of carbon dioxide emissions from fossil fuel combustion and cement production, but these only constituted  55% of global greenhouse gas (GHG) emissions (weighted by global warming potential) in 1970 and 65% in 2010. There has been much less analysis of the drivers of greenhouse gases in general and especially of emissions of greenhouse gases from agriculture, forestry, and other land uses, which we call non-industrial emissions in the paper, that constituted 24% of total emissions in 2010.

The graphs show that non-industrial emissions have a different relationship to income than do industrial emissions. However, there is still a positive relationship between the growth rates of the two variables, especially when we give more weight to larger countries as we do in the paper. Increases in the economic growth rate have about half the effect on non-industrial emissions than they have on industrial emissions.

In both of these graphs China is the large circle on the right. The country with highest non-industrial emissions is Indonesia, which is the largish circle above and to the right of China in the second graph.

We econometrically analyze the relationship between both industrial and non-industrial greenhouse gas emissions and economic growth and other potential drivers for 129 countries over the period from 1971 to 2010. As in Anjum et al., our method combines the three main approaches in the literature to investigating the evolution of emissions and income. We find that economic growth is a driver of both industrial and non-industrial emissions, though growth has twice the effect on industrial emissions. Both sources of emissions decline over time though this effect is larger for non-industrial emissions. There is also convergence in emissions intensity for both types of emissions but given these other effects there is again no evidence for an environmental Kuznets curve.

Monday, March 23, 2015

Telstra Internet

Back in 2010 I reported on the speed of the internet at home in Canberra and from my office on the ANU campus.

I just moved house and because service with iiNet was so bad and getting worse we switched to Telstra internet service. The speed is much, much higher:

The download speed is more than 8 times higher and the upload speed almost 4 times higher when accessing a server in Canberra. Accessing a server in San Jose, California:

downloading is more than 5 times faster and uploading 4 times faster.

Saturday, March 14, 2015

Seminar @ Arndt-Corden 17 March

I am giving a seminar at Arndt-Corden on Tuesday 17th March at 2pm (Seminar Room B, Coombs Building, ANU) titled: "Directed Technical Change and the British Industrial Revolution". The abstract isn't entirely accurate any more - well specifically you won't see me talk about the last two sentences as we don't use a Monte Carlo analysis and we left the low elasticity of substitution for further research. We (myself, Jack Pezzey, and Yingying Lu) are close to having a paper that we are ready to put out as a working paper and submit to a journal. So, am looking forward to getting some useful comments to help us get there.

Wednesday, March 11, 2015

Kander et al. Paper on National Greenhouse-Gas Accounting in Nature Climate Change

Astrid Kander and coauthors at Lund and the University of New South Wales have a paper in Nature Climate Change that proposes a new way to account for embodied carbon in trade that improves on existing measures of consumption based emissions. The collaboration with UNSW was sparked when Astrid gave a presentation at Crawford School in 2012 on the topic, which was attended by Tommy Wiedmann who was then at CSIRO but moved soon after to UNSW. Astrid was visiting ANU to work on our ARC project.

The most common way to compute carbon emissions is based simply on where the emissions are produced. These are called production based emissions (PBA). It is often argued though that this approach overly penalizes countries that export emissions intensive goods and makes countries that import these goods look like their emissions are low when they benefit from emissions intensive production elsewhere. Consumption based emissions (CBA) count all the emissions produced by a country's consumption wherever in the world the goods consumed were produced. Usually, developed countries look more carbon intensive and developing countries less carbon intensive on this basis than when using production based emissions. The following Figure from Kander et al. shows that in the European Union and the USA consumption based emissions exceed production based emissions and vice-versa in China:

But if developed countries tried to produce all their imported goods at home, it is likely that their production techniques would be less emissions intensive than those in the countries that they are importing from. So, consumption based emissions accounting gives a biased view of how much developed countries have managed to reduce emissions by offshoring production. Also, if consumption based emissions were used to apportion world responsibility for reducing emissions the only strategy an importer would have to reduce emissions accounted this way is to stop importing and produce domestically which might not be economically efficient, while the exporter has no incentive to cut these emissions.

However, accounting for emissions embodied in imports based on how much carbon would be emitted if they were produced in the importing country will underestimate total global emissions and so if we want a system of apportioning emissions fairly and usefully for global climate policy purposes it is not so useful.

Kander et al.'s approach deals with the incentive issue. They measure embodied emissions in imports in the same way as conventional CBA. However, they account for exports using the world average emissions intensity for the given good to deduct emissions from exporters instead of deducting the actual emissions produced. This reduces the emissions total for exporters who produce in a low emissions intensive way and increase the emissions of emissions intensive exporters compared to CBA. These technology adjusted consumption based (TCBA) emissions do sum to world total emissions. All exporters now have an incentive to reduce their exports emissions intensity if they were held responsible for their TCBA emissions. The resulting TCBA per capita emissions are shown in the map below and the graphs above.

On this basis emissions per capita in Europe are even less than production based emissions while in the USA they are similar to consumption based emissions. Australia also doesn't look too good on the map. On the other hand, in China TCBA emissions are intermediate between CBA and PBA emissions. The strong performance of Europe is because they have lower than average emissions intensity for the products they export. The latter means that world average emissions for those products is deducted from Europe's balance but their actual emissions for producing those products is lower than that.

The biggest "winners" are Austria, Ireland, and Belgium, which look much more emissions intensive under CBA than under PBA but much less emissions intensive under TCBA.

Astrid discusses the rationale for their approach further in this news article.

Sunday, March 8, 2015

Energy Prices, Growth, and the Channels in Between: Theory and Evidence

Lucas Bretschger has an interesting new paper in Resource and Energy Economics titled: "Energy prices, growth, and the channels in between: Theory and evidence". The paper argues that countries with higher energy use per capita grow slower in the long-run though reductions in energy use lower output in the short-run. The long-run effect is due to an induced increase in capital accumulation and because the model is similar to AK endogenous growth models, innovation. The paper is motivated by the stylized fact that in a sample of 37 countries, countries with higher per capita energy use grow slower. The sample includes mostly developed countries but also China and India.

This negative correlation is, however, easy to explain in terms of catch-up growth dynamics. As we show in our stylized facts paper, there is a strong positive correlation between the level of GDP per capita and the level of energy use per capita. Per capita income in countries such as China and India has risen faster than in the developed countries due to the fact that they are poorer and undergoing catch-up growth. This results in a spurious negative relationship between energy use per capita and the rate of economic growth.

This is not to say at all that Bretschger's theoretical model is wrong, but the motivation can easily be explained in another way. In fact, I'm very sympathetic to the idea that plentiful energy resources could slow the rate of economic growth as I discussed in my presentation at the AARES conference in Rotorua and my upcoming Arndt-Corden seminar on 17th March.

Bretschger also estimates an econometric model that is loosely related to his theoretical model (for example, using energy quantity rather than price due to a lack of internationally comparable data - a big problem for energy economics) that regresses the investment/output ratio on energy intensity and GDP (there are additional equations). It is not surprising that reduced energy intensity could encourage increased investment if it represents increased energy efficiency - this is one of the factors in macro-level rebound as in Harry Saunders (1992) model.

The bottom line is that the energy-output relationship is quite complicated and is probably not at all well captured by reduced form time series models. Bretschger is also making this point with his paper.

Sunday, February 22, 2015

How Has Research Assessment Changed the Structure of Academia?

Does measuring something change it?  In quantum mechanics measurement disturbs what is being measured, which is referred to as the observer effect. The same is often true in social systems, especially of course when measurement is attached to rewards. The UK and Australia have been conducting periodical research assessment exercises - the REF and ERA. In the case of the UK, research assessment started almost three decades ago. In Australia, the first research assessment was only conducted in 2010 but the founding of the ARC in 1988 and its independence in 2001 are both milestones in the road to increased emphasis on competition in research in Australia.

Johnston et al. (2014) show that the total number of economics students has increased in UK more rapidly than the total number of all students, but the number of departments offering economics degrees has declined, particularly in post-1992 universities. Also, the number of universities submitting to the REF under economics has declined sharply with only 3 post-1992 universities submitting in the latest round. This suggests that the REF has driven a concentration of economics research in the more elite universities in the UK. BTW the picture above is of the Hotel Russell, which the Russell Group of British universities is named after.

Neri and Rodgers (2014) investigate whether the increased emphasis on research in Australia has had the desired effect in the field of economics. They investigate the output of top economics research by Australian academics from 2001 to 2010. By constructing a unique database of 26,219 publications in 45 top journals, they compare Australia’s output internationally, determine whether Australia’s output increased, and rank Australian universities based on their output. They find that Australia’s output, in absolute and relative terms, and controlling for differences in page size and journal quality, increased and, on a per capita basis, is converging to the levels of the most research-intensive countries. Finally, they find that the historical dominance of the top four universities is diminishing. The correlation between the number of top 45 journal articles published in 2005-2010 and the ERA 2012 ranking is 0.83 (0.78 for 2003-8 and ERA 2010).


Johnston, J., Reeves, A. and Talbot, S. (2014). ‘Has economics become an elite subject for elite UK universities?’ Oxford Review of Education, vol. 40(5), pp. 590-609.

Neri, F. and Rodgers, J. (2014). ‘The contribution of Australian academia to the world’s best economics research: 2001 to 2010’, Economic Record.

Peer Review vs. Citation Analysis in Research Assessment Exercises

Existing research finds strong correlations between the rankings produced by UK research assessment exercises (RAE) and bibliometric analyses for several specific humanities and social science disciplines (e.g. Colman et al., 1995; Oppenheim, 1996; Norris and Oppenheim, 2003) including economics (Süssmuth et al., 2006). Clerides et al. (2011) compare the 1996 and 2001 RAE ratings of economics departments with independent rankings from the academic literature. They find RAE ratings to be largely in agreement with the profession’s view of research quality as documented by independent rankings, although the latter appear to be more focused on research quality at the top end of academic achievement. This is because most rankings of departments in the economics literature are based on publications in top journals only, which lower ranked departments have very few of.

Mryglod et al. (2013) analyse the correlations between the values of Thomson Reuters Normalised Citation Impact (NCI) indicator and RAE 2008 peer-review scores in several academic disciplines, from the natural to social sciences and humanities. The NCI computes the normalized impact factor across a unit of assessment (an academic discipline at a given university) in the RAE based on only the publications actually submitted to the RAE. Mryglod et al. (2013) compute both average (or quality) and total (or strength) values (average multiplied by number of staff submitted to the RAE) of these two indicators for each institution. They find very high correlations for the strength indicators for some disciplines and poor correlations at for the quality indicators for all disciplines. This means that, although the citation-based scores could help to describe institution level strength (which is quality times size), in particular for the so-called hard sciences, they should not be used as a proxy for ranking or comparison of research groups. Moreover, the correlation between peer-evaluated and citation-based scores is weaker for the “soft” sciences. Spearman rank correlation coefficients for their quality indicators range from 0.18 (mechanical engineering) to 0.62 (chemistry). However for strength the correlations range from 0.88 (history and sociology) to 0.97 (biology). This is because quality is correlated with size and so the two factors reinforce each other.

Mryglod et al. (2014) attempt to predict the 2008 RAE retrospectively and the 2014 Research Excellence Framework (REF) before its results were released. They examined biology, chemistry, physics, and sociology. Of the indicators they trialled, they found that the departmental h-index had the best fit to the 2008 results. Departmental h-index is based on all publications published by a department in the time window assessed by the relevant assessment exercise. The rank correlation ranged from 0.83 in chemistry to 0.58 in sociology. They find that the correlation with the RAE for the immediate h-index is as good as the correlation in later years with the h-index of the same set of publications.

Bornmann and Leydesdorff (2014) argue that one of the downsides of bibliometrics as a research assessment instrument is that citations take time to accumulate while research assessment exercises are designed to assess recent performance:

“This disadvantage of bibliometrics is chiefly a problem with the evaluation of institutions where the research performance of recent years is generally assessed, about which bibliometrics—the measurement of impact based on citations—can say little…. the standard practice of using a citation window of only 3 years nevertheless seems to be too small.” (1230)

They argue further that bibliometrics:

“can be applied well in the natural sciences, but its application to TSH (technical and social sciences and humanities) is limited.” (1231)

But rather than assuming that peer review is the preferred approach to research assessment and citation analysis should only be used to reduce cost, we can ask whether the review conducted by research assessments such as the REF and the Australian ERA meets the normal academic standards for peer review. Research does show that peer review at journals has predictive validity for the citations that will be received by accepted papers compared to those received by rejected papers. However, evidence for the predictive validity of peer review of grant and fellowship applications is more mixed (Bornmann, 2011). Therefore, further research is warranted on the use of citation analysis to rank academic departments or universities in research assessment exercises. Sayer (2014) argues that the peer review undertaken in research assessment exercises does not meet normal standards for peer review. He compares university and national-level REF processes against actual practices of scholarly review as found in academic journals, university presses, and North American tenure procedures. He finds that the peer review process used by the REF falls far short of the level of scrutiny or accuracy of these more familiar peer review processes. The number of items each reviewer has to assess alone means that the review cannot be of the same quality as reviews for publication. And reviewers will have to assess much material outside their area of specific expertise. Sayer argues that though metrics may have problems, a process that gives such extraordinary gatekeeping power to individual panel members is far worse.

Given the large number of items that panels need to review they are likely to focus on the venue of publication and at least in business and economics handy mappings of journals to REF grades exist (Hudson, 2013). Regibeau and Rockett (2014) build imaginary economics departments entirely composed of Nobel Prize winners and evaluate them using standard journal rankings geared to the UK RAE. Performing the same evaluation on existing departments, they find that the rating of the Nobel Prize departments does not stand out from other good departments. Compared to recent research evaluations, the Nobel Prize departments’ rankings are less stable. This suggests a significant effect of score “targeting” induced by the rankings exercise. They find some evidence that modifying the assessment criteria to increase the total number of publications considered can help distinguish the top. But if departments composed entirely of Nobel Prize winners perform worse than current departments then it is hard to know what such assessment means.

Sgroi and Oswald (2013) examine how research assessment panels could most effectively use citation data to replace peer review. They suggest a Bayesian approach that uses prior information on where a item was published combined with observations on citations to derive a posterior distribution for the quality of the paper. We could then estimate, for example, what is the probability that a paper belongs in the 4* category given where it was published and the early citations it has received. Stern (2014) and Levitt and Thelwall (2011) show that the journal impact factor has strong explanatory power in the year of publication but that this declines very quickly as citations accumulate. So, this approach would be most useful for papers published in the last year or two before the assessment, but for earlier research outputs the added value over simply counting citations would be minimal.


Bornmann, L. (2011) ‘Scientific peer review’, Annual Review of Information Science and Technology, vol. 45, pp. 199‐245.

Bornmann, L. and Leydesdorff, L. (2014). ‘Scientometrics in a changing research landscape’, EMBO Reports, vol. 15(12), pp. 1228–32.

Clerides, S., Pashardes, P. and Polycarpou, A. (2011) ‘Peer review vs metric-based assessment: testing for bias in the RAE ratings of UK economics departments’, Economica, vol. 78(311), pp. 565–83.

Colman, A. M., Dhillon, D. and Coulthard, B. (1995) ‘A bibliometric evaluation of the research performance of British university politics departments: Publications in leading journals’, Scientometrics vol. 32(1), pp. 49-66.

Hudson, J. (2013). ‘Ranking journals’, Economic Journal, vol. 123, pp. F202-22.

Levitt, J.M. and Thelwall, M. (2011). ‘A combined bibliometric indicator to predict article impact’, Information Processing and Management, vol. 47, pp. 300–8.

Mryglod, O., Kenna, R., Holovatch, Y. and Berche, B. (2013). ‘Comparison of a citation-based indicator and peer review for absolute and specific measures of research-group excellence’, Scientometrics, vol.97, pp. 767–77.

Mryglod, O., Kenna, R., Holovatch, Y. and Berche, B. (2014). Predicting Results of the Research Excellence Framework Using Departmental H-Index, arXiv:1411.1996v1.

Norris, M. and Oppenheim, C. (2003) ‘Citation counts and the research assessment exercise V: Archaeology and the 2001 RAE’, Journal of Documentation, vol. 59(6): pp. 709-30.

Oppenheim, C. (1996) ‘Do citations count? Citation indexing and the research assessment exercise’, Serials, vol. 9, pp. 155–61.

Regibeau, P. and Rockett, K.E. (2014). ‘A tale of two metrics: Research assessment vs. recognized excellence’, University of Essex, Department of Economics, Discussion Paper Series 757.

Sayer, D. (2014). Rank Hypocrisies: The Insult of the REF. Sage.

Sgroi, D. and Oswald, A.J. (2013). ‘How should peer-review panels behave?’ Economic Journal, vol. 123, pp. F255–78.

Stern, D.I. (2014). ‘High-ranked social science journal articles can be identified from early citation information’, PLoS ONE, vol. 9(11), art. e112520. 

Süssmuth, B., Steininger, M. and Ghio, S. (2006) 'Towards a European economics of economics: Monitoring a decade of top research and providing some explanation', Scientometrics, vol. 66(3), pp. 579-612.

Tuesday, February 10, 2015

Arik Levinson Seminar 24 February at ANU

Arik Levinson will be presenting at the Arndt Corden Seminar at 2pm on 24th February (Seminar Room B in the Coombs Building). The Freakonomics Radio Show just did a podcast on the paper which he is going to be presenting.

Friday, January 23, 2015

The Rebound Effect

Working on an article for New Palgrave. Here is a draft of the section on the rebound effect:

The Rebound Effect

Energy saving innovations reduce the cost of providing energy services such as heating, lighting, industrial power etc. This reduction in cost encourages consumers and firms to use more of the service. As a result energy consumption usually does not decline by as much as the increase in energy efficiency implies. This difference between the improvement in energy efficiency and the reduction in energy consumption is known as the rebound effect. Rebound effects can be defined for energy saving innovations in consumption and production. In both cases the increase in energy use due to increased use of the energy service where an efficiency improvement has happened is called the direct rebound effect. For consumer use of energy estimated rebound effects are usually small typically in the range of 10-30% (Greening et al., 2000; Sorrell et al., 2009). Roy (2000) argues that because high quality energy use is still small in households in India, demand is very elastic, and thus rebound effects in the household sector in India and other developing countries can be expected to be larger than in developed economies. In the case of energy efficiency improvements in industry the rebound effect at the firm level could be large as the form could greatly increase their sales as a result of reduced costs. However, under perfect competition for an industry supplying domestic demand it is much harder for the industry as a whole to expand output and so the direct rebound effect would be more limited. Rebound effects are likely to be larger for export industries that have more opportunity to expand production (Grepperud and Rasmussen, 2004; Allan et al., 2007; Linares and Labandeira, 2010).

As a result of the reduction in the cost of the energy service consumers will demand less of substitute goods and more of complementary goods. These include other energy services. Firms will make similar changes in their demands for inputs. There will also be additional repercussions throughout the economy – non-energy goods whose demand has increased require energy in their production; the fall in energy demand may lower the price of energy (Gillingham et al., 2013; Borenstein, 2015) increasing energy use again; and the efficiency improvement is a contribution to an increase in total factor productivity, which tends to increase capital accumulation and economic growth that results again in greater energy usage (Saunders, 1992). These additional effects are called indirect rebound effects, though the latter two may be treated separately as “macro-level rebound effects” (e.g. Howarth, 1997). Direct and indirect rebound effects together sum to the economy-wide rebound effect.

Estimates of the economy-wide rebound effect are few in number (e.g. Turner, 2009; Barker et al., 2009; Turner and Hanley, 2011) and vary widely (Stern, 2011; Saunders, 2013; Turner 2013). At the economy-wide level “backfire”, where energy use increases as a result of an efficiency improvement, or even “super-conservation” where the rebound is negative are both theoretically possible (Saunders, 2008; Turner, 2009). It is usually assumed that the indirect rebound is positive and that the economy-wide rebound will be larger in the long run than in the short run (Saunders, 2008). Turner (2013) argues, instead, that because the energy used to produce a dollar’s worth of energy is higher than the embodied energy in most other goods, the effect of consumers shifting spending to goods other than energy will mean that the indirect rebound could be negative and the economy-wide rebound may also be negative in the long run. Borenstein (2015) presents further arguments for negative rebounds.

All evidence on the size of the economy-wide rebound effect to date depends on theory-driven models, which have limited empirical validation. Turner (2009) finds that, depending on the assumed values of the parameters in a simulation model, the rebound effect for the UK can range from negative to more than 100%. Barker et al. (2009) provide the only estimate of the global rebound effect, estimating the rebound from a set of IEA recommended energy efficiency policies at 50%.


Allan, G., Hanley, N., McGregor, P., Swales, K., Turner, K. 2007. The impact of increased efficiency in the industrial use of energy: A computable general equilibrium analysis for the United Kingdom. Energy Economics 29: 779–798.

Barker, T., Dagoumas, A. and Rubin, J. 2009. The macroeconomic rebound effect and the world economy. Energy Efficiency 2: 411-427.

Borenstein, S. 2015. A microeconomic framework for evaluating energy efficiency rebound and some implications. Energy Journal 36(1): 1-21.

Gillingham, K., Kotchen, M. J., Rapson, D. S. and Wagner, G. 2013. The rebound effect is overplayed. Nature 493: 475-476.

Greening, L. A., Greene, D. L. and Difiglio, C. 2000.Energy efficiency and consumption - the rebound effect - a survey. Energy Policy 28: 389-401.

Grepperud, S. and Rasmussen, I. 2004. A general equilibrium assessment of rebound effects. Energy Economics 26: 261-282.

Howarth, R. B. 1997. Energy efficiency and economic growth. Contemporary Economic Policy 25: 1-9.

Linares, P. and Labandeira, X. 2010. Energy efficiency: Economics and policy. Journal of Economic Surveys 24(3): 583-592.

Roy, J. 2000. The rebound effect: some empirical evidence from India. Energy Policy 28: 433-438.

Saunders, H. D. 1992. The Khazzoom-Brookes postulate and neoclassical growth. Energy Journal 13(4): 131-148.

Saunders, H. D. 2008. Fuel conserving (and using) production functions. Energy Economics 30: 2184–2235.

Saunders, H. D. 2013. Historical evidence for energy efficiency rebound in 30 US sectors and a toolkit for rebound analysts. Technological Forecasting & Social Change 80 (2013) 1317-1330.

Sorrell, S., Dimitropoulos, J., Sommerville, M. 2009. Empirical estimates of the direct rebound effect: A review. Energy Policy 37: 1356–1371.

Stern, D. I. 2011. The role of energy in economic growth. Annals of the New York Academy of Sciences 1219: 26-51.

Turner, K. 2009. Negative rebound and disinvestment effects in response to an improvement in energy efficiency in the UK economy. Energy Economics 31: 648-666.

Turner, K. 2013. “Rebound” effects from increased energy efficiency: a time to pause and reflect. Energy Journal 34(4): 25-43.

Turner, K. and Hanley, N. 2011. Energy efficiency, rebound effects and the Environmental Kuznets Curve. Energy Economics 33: 722-741.

Sunday, January 11, 2015

The Industrial Revolution Remains One of History's Great Mysteries?

Following on from my previous post, Clark's chapter reviews possible reasons for why the industrial revolution happened in England when it did. He rules out theories based on improved institutions, increased human capital in terms of an increase in quality of children instead of quantity, and increased population driving higher innovation rates (why not China then?). Surprisingly he doesn't cite either Allen's or Wrigley's recent books, though he does reference Hansen and Prescott (2002) - he doesn't like it. So energy doesn't get a mention except to reiterate the arguments of Clark and Jacks (2007). He concludes that: "The Industrial Revolution remains one of history's great mysteries." (p260). But why should we expect just one of these factors to explain the Industrial Revolution. Instead, I think several factors together might very well explain it.

Does Age Heaping Mean the Romans were Innumerate?

The system of dating years since some ancient point in the past used today by the Western, Islamic, and Hebrew Calendars among others makes it much easier to remember how old you are. If you know you were born in 1964 or 5725 and know that this year is 2015 or 5775, it's easy to work out how old you are. But in ancient Rome it seems that it was not even common to date years by the number of years the emperor had ruled, let alone since the foundation of Rome. It was more common to name years by the names of the consuls in office. So, it's not surprising that there is a lot of age-heaping on Roman tombstones. Gregory Clark argues that this shows that Romans were very innumerate. That might be partly true, but the lack of a proper dating system also needs to be taken into account.

Tuesday, December 30, 2014

My Year in Review 2014

I've been doing these annual reviews since 2011, they're mainly an exercise for me to see what I accomplished and what I didn't in the previous year. It is now a full year since I ended my term as research director at the Crawford School. As a result, it has been a really productive year research-wise :)

I published five articles in the following journals: PLOS ONE, Biomass and Bioenergy, Energy Economics, The Energy Journal, and Climatic Change, and we have a paper in press at The Energy Journal. We also released three working papers that aren't yet published: "Modeling the Emissions-Income Relationship Using Long-run Growth Rates", "Substitutability and the Cost of Climate Mitigation Policy", "Global Energy Use: Decoupling or Convergence". There are four more papers that we have sent for review but have not yet posted as working papers.

We also published our edited book of classic papers on the economics of climate change with Edward Elgar. There is also Chapter 5 of the IPCC Report on trends and drivers of emissions and a small piece on the environmental Kuznets curve and there is an updated review of the EKC, which will be published in the Elsevier Online Resources.

The release of the IPCC 5th assessment report in April was of course a big event and I appeared on TV and radio several times - first on the release day and then in some follow-up coverage on the supposed cover up in the Summary for Policymakers.

ABC News24

This was the final year of our ARC grant (actually, March 2015 is formally the end of the project). Astrid Kander visited Sydney in February to work with researchers at UNSW and Jack Pezzey and I went to meet up with her and work on our project. She rented a house for her and two other Swedish researchers close to Coogee Beach (and to UNSW), so it was a very nice research trip :) The weather wasn't quite as good when I visited Lund in November for a week!

Coogee Beach, Sydney

I also visited England and Germany on my October-November trip giving seminars at LSE, Lund, and University of Kassel. That was my third international trip of the year. In June-July I did a round the world trip including the IAEE conference in New York City, the Atlantic Workshop in A Toxa, and the World Congress of Environmental and Resource Economics in Istanbul. In September I attended the IAEE Asia meeting in Beijing as well as a workshop at Tsinghua University. The AARES Conference in Port Macquarie, NSW rounds off the conference list and I also gave a couple of seminars in Canberra in the first half of the year.

 Hagia Sophia, Istanbul

Two researchers visited me to collaborate - Zsuzsanna Csereklyei in January and February and Chunbo Ma in April. I wrote an ARC Discovery proposal with Zsuzsanna, which wasn't funded but we were in the top 10% of the unfunded proposals and so we'll give it another go. Chunbo came to work on the current ARC grant. We have now submitted a paper on substitution elasticities in China, which I presented at the Tsinghua workshop in September.

The special issue of Energies on "Energy Transitions and Economic Change", which I guest edited is now completed with fourteen papers are already published including the final paper by Astrid Kander and colleagues.

It was my last time teaching the introductory micro-economics class The Economic Way of Thinking 1. This course was great for the positive feedback I got from some of the students on the course. All the students are from developing countries and many are a bit "scared" of math and economics. After going through this course a lot of students feel much more confident dealing with this kind of material. In the coming year I will be teaching quantitative methods to environmental studies students instead. I also taught my energy economics course again and will continue to teach it in the future. It is being rebranded next year as an economics course, IDEC8029, instead of a general Crawford School course (CRWF8017).

It's hard to believe, but I posted more than 100 blogposts this year. The most popular was this one, a close runner-up is the post on the animated gif of energy use and growth, which we produced at James Hamilton's suggestion. I met Hamilton at the IAEE meeting in New York. I also got much more involved with Twitter this year. Mostly, I tweet my blogposts, but also tweet short items, which don't really need comment or analysis, that in the past I might have blogged about.

Energy and Growth: The Animated GIF

As always, it is possible to predict some of the things that will be happening in the coming year. I expect a couple more papers will get completed over the summer. Also, we are going to resubmit the ARC proposal, hopefully this time successfully. There will also be a couple of book chapters surveying the energy and growth topic. One for Palgrave. I've submitted abstracts to a bunch of conferences in Rotorua (AARES), Perth (at Curtin U), Leeds (ESEE), and Antalya (IAEE) and will likely submit to the EAERE conference in Helsinki. Not sure how many of these I can actually go to. Maybe my coauthors will present at some of them. Hopefully Donglan Zha will get funding to visit Crawford from the middle of next year.

Wednesday, December 24, 2014

Energies Special Issue Update

There are now thirteen articles in the special issue, which I edited. The latest two are by Peter O'Connor and Cutler Cleveland and Juliana Subtil Lacerda and Jeroen van den Bergh. There is only one paper still to be published, which is by Astrid Kander and coauthors. P.S. Astrid's paper was published two days after I posted this!

Wednesday, December 17, 2014

Global Energy Use: Decoupling or Convergence?

I have another new working paper coauthored with Zsuzsanna Csereklyei out titled: "Global Energy Use: Decoupling or Convergence?". This paper follows up on our paper on the the stylized facts of energy and growth using the methods from our paper on modeling the emissions-income relationship using long-run growth rates.
In particular, we focus on the stylized facts that there is a stable relationship between energy use and GDP per capita over time and that there has been convergence in energy intensity over time.

The following graph shows the relationship between the long-run growth rates of energy use and GDP per capita from 1971 to 2010:
As we saw in our previous paper, higher economic growth rates are associated with higher rates of growth in energy use, though there is quite a lot of variation in individual countries. As the intercept of the regression line is zero, on average there is no time effect that is reducing energy use across all countries in the absence of economic growth. On the other hand, many developed countries like the UK, Sweden, or even the United States have seen declines or little increase in energy use per capita in recent decades. So, what can explain that?

Our model adds additional explanatory variables to the regression illustrated above. To test whether there is decoupling, so that growth has less effect or even a negative effect on energy use at higher income levels we include an interaction term between the growth rate and level of income per capita. This is the same idea as the test for the environmental Kuznets curve in the Anjum et al. paper. We find that the regression coefficient for this interaction term is actually positive! So, actually growth has larger rather than smaller effects on energy use in higher income countries. However, we find that the level of income has a negative effect on the growth rate of energy use. This means that at higher income levels there is an improving energy efficiency effect so that energy use declines over time ceteris paribus. We call this "weak decoupling". The following graph shows the contribution of these and other effects to the growth in energy use in different groups of countries:
Though, as shown by the black dots, the growth rate of energy use  per capita is highest in upper middle income countries, the contribution of economic growth is greater in high income countries. But this positive effect of growth is offset by "weak decoupling" and other effects.

The most important of these other effects globally is convergence. Countries that had high energy intensities at the beginning of the period saw declines in energy intensity, ceteris paribus. But, this effect was most important in the low income countries, some of which were the most energy intensive in our sample in 1971. In the high income countries, convergence raised energy use on average. But in the US and Canada it contributed -1.0% and -0.9% p.a., respectively, to reducing energy use. So, there is a lot of variation across countries.

Projections and forecasts of future energy use should not, therefore, assume that economic growth will be associated with decreased energy use in the future. Instead, the scale effect seems to be alive and well. On the other hand, there appear to be improvements in energy efficiency across high income countries irrespective of their growth rates or their initial level of energy intensity. These would tend to moderate the growth in energy use as countries get richer at the upper end of the income continuum. At the lower end of the income continuum the same effects serve to raise energy intensity. But, some of the major reductions in energy intensity in countries, such as in the United States and China, have probably been the result of convergence towards the global mean, and so are unlikely to be reproduced in the future.

On the more technical side there are a couple of innovations in this paper too. We extend the method we used in the growth rates paper to allow for a spatially correlated error term. If there are omitted variables which are spatially correlated and the explanatory variables are also spatially correlated then it is likely that the two are correlated and regression coefficient estimates will be inconsistently estimated. To deal with this problem we use an approach called spatial filtering. This removes the spatial autocorrelation by adding additional variables to the regression which model the spatial process. These are in fact the eigenvectors of a transformation of the spatial weighting matrix. With 93 countries there are 93 eigenvectors, so the tricky part is deciding which of these eigenvectors to include in the regression. Tiefelsdorf and Griffith (2007) developed a procedure to do this, which we use.

Another issue is that if we want to give our model a causal interpretation, then we have to assume that GDP growth causes growth in energy use and not vice versa. Obviously changes in energy use might also cause GDP. We argue though that the latter effect is probably quite small compared to the effect of GDP on energy and so the estimated effect of GDP on energy is only biased upwards by a relatively small amount. The income elasticity of energy is likely to be close to unity whereas the elasticity of GDP w.r.t. to energy might be only 0.05. This is possibly one reason why it has been so hard for researchers to find robust signs of Granger causality from energy use to GDP. On other hand, this is maybe why a simple naive regression of GDP on energy use appears to find a very large effect of energy on GDP. The estimated regression coefficient is biased upwards by the effect of income on energy demand.

Tuesday, December 16, 2014

New Research Shows that Release of Carbon in PETM was More Gradual

Following up on my post last year on research that the PETM was probably caused by an impact. Latest research, published in Nature Geoscience, shows that, no, the release was much more gradual. I wonder how these two pieces of research can be reconciled?

Tuesday, November 18, 2014

How Ambitious is China's Proposal to Peak CO2 Emissions by 2030?

A few days ago China and the US jointly announced emissions targets for 2030. China proposes that their carbon emissions will peak by not later than 2030. How ambitious is this goal? In our 2010 paper in Energy Policy, Frank Jotzo and I asked how ambitious China's 2020 target to reduce emission intensity by 40-45% between 2005 and 2020 was. We concluded that it represented significant effort beyond expected intensity reductions under business as usual.

In a recent paper Xiliang Zhang and coauthors project Chinese emissions under three scenarios. Under a no policy scenario, emissions rise to 16.5 billion tonnes (Gt) in 2030 and continue to rise throughout the century. Under their "continued effort" scenario where current policy initiatives are continued, emissions rise to 11.8 Gt in 2030 and peak in 2045. Finally, under their accelerated effort scenario, emissions rise to 10.2 Gt in 2030 where they peak. So, on this basis, China's proposal does constitute a new accelerated effort.

Another way of looking at these scenarios is in terms of the rate of reduction in emissions intensity in 2030. The rates are -1.9%, -3.4%, and -4.1% respectively. China's 2020 emissions intensity target represents a 3.6% annual rate of reduction in emissions intensity from 2005 to 2020. So, by this metric the new target represents an increase in effort over the current policies.

Monday, November 17, 2014


I just signed up for Figshare. In case you haven't heard about it yet, it is a site for sharing all kinds of research data. I uploaded the citation data I used in my 2013 article in the Journal of Economic Literature. This was a lot easier than adding data to my university's data repository so, in future, I think I will use Figshare exclusively for larger datasets I want to make public. The service is free and you get a DOI for your dataset.

Wednesday, November 12, 2014

Article Published Today in PLoS ONE

My paper "High-Ranked Social Science Journal Articles Can Be Identified from Early Citation Information" was published today in PLoS ONE. For background on the paper, check out my blogpost or this story on the Crawford School website.

I'm travelling tomorrow to Kassel where I will be working with Stephan Bruns on what we think is a really awesome (Stephan's words :)) extension to this paper. We are also hoping to finish an econometric theory paper we are writing.

Tuesday, November 11, 2014

Stylized Facts Paper Accepted for Publication

My paper with Zsuzsanna Csereklyei and Mar Rubio: "Energy and Economic Growth: The Stylized Facts" has been accepted for publication in the Energy Journal. I've already blogged quite a bit about the paper so won't repeat that here. What is new is that we also now have a working paper version available. The working paper version has color figures, which I think are prettier and easier to understand in some cases than the black and white ones we had to use for publication.

Friday, October 24, 2014

Odds of Becoming a Professor

This graphic is from a 2010 UK report and is based on UK data. Only 0.45% of PhDs eventually become a full professor. I didn't think the odds were quite that low. Of course, as in Australia, full professor is a higher rank than it is in the US as we have 4 rather than 3 academic ranks. Another interesting report I recently saw on Australian PhDs. Apparently in 2011 Australia graduated about 7000 PhDs which is about 1/7 of the US figure, even though Australia has 1/15 of the US population. And the number of students starting PhDs in the year was 11,000.

Tuesday, October 21, 2014

Five Minute Paper

You may have heard about the Three Minute Thesis. Now we have the Five Minute Paper. Actually, it's called Elsevier Audioslides. Authors of articles in Elsevier journals are invited to create voiced over slide presentations about their papers to be hosted on Elsevier's website. The maximum length of recording is five minutes. As my presentation at LSE next week will cover my recent paper with Astrid Kander (as well as current work), I thought I could use some of the slides I made for an audioslides presentation on our paper. I didn't bother writing a script and just made it up as I went along. But that's the way it goes in a conference presentation too and, of course, in the Three Minute Thesis competition.

Here is the result.

I've also got an invite to do one for my paper in Biomass and Bioenergy. But as I've never presented that paper, I would have to make up the slides from scratch and I'm not sure it's worth the effort. I think I'll ask my coauthor if he wants to do it :)

Tuesday, October 14, 2014

Seminar at University of Kassel

I promised more details on my seminar at University of Kassel: here they are. I will present our paper on modeling the emissions income relationship using long-run growth rates. My presentation will be at 2pm on 18 November in Sitzungsraum K33/FB07. If you need more details about location, ask Stephan Bruns who is organizing the "Empirical Workshop on Energy, Environment, and Climate Change" of which this talk is part. The workshop starts at 10 am and there will also be presentations by Heike Wetzel, Andreas Ziegler, Astrid Dannenberg, and Stephan.

New Dimensions in Ecological Economics: Elgar E-Book

Our edited book New Dimensions in Ecological Economics: Integrated Approaches to People and Nature is now available as an E-Book from Edward Elgar. This book was based on the 2000 ISEE international conference in Canberra that Mike Young and I organized.

Environmental & Resource Economics Acceptance Rate 2013

Just got an e-mail from the journal noting that they got just over 600 submissions in 2013. They have already reached that level at this point of 2014. Back in 2004 they got less than 200 submissions. This is a common trend at many journals including Ecological Economics, where I am an associate editor. The email from ERE also notes that their impact factor is now 1.7 and this too has risen over time (0.6 in 2005). One of the reasons for that is the increased coverage of economics journals in the Journal Citation Reports. The number covered doubled in the last decade and that increases the opportunity to get cited in outlets covered by the JCR. One thing, ERE don't report on is their acceptance rate, but it is easy to calculate. According to the JCR they published 83 articles in 2013. Therefore, the acceptance rate is 13%.

I previously reported that the acceptance rate at ERE was 21%. So, this is a big drop. This is also a common trend.

Thursday, October 9, 2014

Interested in Graduate Study at ANU?

Come along to the information evening next week at University House. At 6:30pm in the Common Room, Frank Jotzo, Amanda Smullen, Paul Burke, and Sue Thompson will talk about what you can study and why at the Crawford School.

Tuesday, September 30, 2014

Update on Energies Special Issue

We now have nine papers published in the special issue of Energies on energy transitions and economic change and there are more to come. The latest paper is by Robert Kaufmann on the end of cheap oil and the implications for the United States and the former Soviet Union. This was one of the invited papers. The other published so far was the paper by Steve Sorrell. Also recently published is a paper by James Kahn et al. on Brazil's plans for expanding hydropower and by Rodriguez-Molina et al. on the smart grid.

Upcoming Seminars

I am giving three seminars in Europe in October and November. First up is 28th October at 1pm at the Grantham Research Institute on Climate Change at the London School of Economics. I will talk about "Energy Transitions and the Industrial Revolution." Then on 12th November at 2:15pm I will talk at the Department of Economic History at Lund University. Topic: "Energy and Economic Growth: The Stylised Facts"  - a topic that blog readers should be pretty familiar with by now.

Finally, I will be presenting at the University of Kassel in Germany on 18th November. More details to come.

Saturday, September 13, 2014

Fuel Choices in Rural Maharashtra Accepted for Publication

My paper with former masters student Jack Gregory was just accepted for publication in Biomass & Bioenergy. Jack is just starting his PhD at University of California, Davis.

This paper went through one of the more tortuous paths to publication, largely because we didn't have any sort of price data, which made the paper less interesting to economics journals. This is where we sent it: World Development (submitted 27 Jan 2012, desk reject, too narrow case study), Environment and Development Economics (referee review), Energy Policy (referee review), Energy (desk reject, too economics focused), Biomass and Bioenergy (revise and resubmit and accept). More than 2.5 years to get it published. But that's not very unusual...

Wednesday, September 10, 2014

Workshop on Research Metrics

I submitted one of the 152 responses to HEFCE's call for evidence on research metrics. BTW, my paper was just accepted by PLoS ONE :) Anyway, HEFCE and the University of Sussex are holding a one day workshop at SPRU on the potential for metrics in research assessment. Register here and see the program here. As I am in Australia, unfortunately I can't attend - I'm actually going to be in England in late October and early November - but maybe some of you can.

Tuesday, September 2, 2014

New Professorial and Research Positions at SPRU, University of Sussex

SPRU (Science Policy Research Unit) at the University of Sussex, UK is embarking on an ambitious new research strategy, focused on long-term transformative change and innovation. As part of this strategy, we are looking to recruit three dynamic, innovative and highly respected academic leaders to join the SPRU team as Professors. In addition, we are seeking to appoint two experienced research staff to join the Research Centre on Innovation and Energy Demand (CIED), led by the Sussex Energy Group at SPRU. The posts are as follows:

Professor of Energy Policy: This person will lead the Sussex Energy Group and will have an outstanding background in energy and climate policy, preferably with an emphasis on innovation and transitions.

Professor in Sustainability Transitions: This person will have an outstanding background in sustainability transitions, history of technology and/or science and technology studies.

Professor in Innovation and Evolutionary Economics: This person will have an outstanding background in evolutionary economics, economics of innovation, institutional economics, economic history and/or development economics.

Senior Fellow in Innovation and Energy Demand: This person will have a strong track record in innovation studies and/or energy and climate policy and will be expected to help shape the Centre’s research programme and design and lead research projects.

 Research Fellow in Innovation and Energy Demand: This person will have a background in innovation studies and/or energy and climate policy and will be expected to design and lead research projects and conduct empirical research.

 Full details of the jobs can be found here:

Monday, September 1, 2014

Citation Data for Citation Prediction Paper Now Available

The data underlying my recent working paper: "High-Ranked Social Science Journal Articles Can Be Identified from Early Citation Information" are now available from the ANU Data Repository. The data set includes most journal articles in economics and political science published in 2006 and included in the Web of Science and the number of citations that received each year through 2012. There is also a worksheet with all economics articles from 1999 too. That's not mentioned in the working paper but is mentioned in the revised version of the article I just resubmitted to the journal. The journal's (PLoS ONE) data policy requires all data to be made available with DOI's if possible. This is definitely the current trend and looks like becoming the norm. For example, Energy Economics requires both data and code to be submitted prior to publication. I have mixed feelings about this. Obviously I am in favor of replicability but putting together datasets costs time and/or money and so it seems a bit unfair to force authors to make their data freely available as the price of publication.

P.S. 9th September
My paper was accepted at PLoS ONE! :)

Saturday, August 30, 2014

"Economic Growth and the Transition from Traditional to Modern Energy in Sweden" to be Published in Energy Economics

We started working on this paper when I visited Sweden in September 2010. It took a while till we were both happy with the paper. Then we submitted it to what I think is the top economic history journal. We got a revise and resubmit. I worked hard to do exactly what the referees wanted but the editor rejected the paper. I think this was a first for me. Of course, I had declined to resubmit papers in the past because I thought the chances were better elsewhere. Then we submitted to another economic history journal who gave us a revise and resubmit too. But this time we decided to not resubmit as it seemed unlikely we could please the referees. So, then I submitted the paper to Energy Economics and got a "minor revisions" and now it is accepted. This is a fairly typical story I think in terms of time taken and submissions made.

Sunday, August 17, 2014

Jakob et al. (2012) Revisited

A recent paper by Jakob et al. (2012) finds that there is decoupling between growth in energy use and growth in GDP in developed countries. The authors regress the first differences between five year period means of log per capita energy use on the same transformation of GDP per capita separately for panels of OECD and non-OECD countries. They have 21 OECD and 30 non-OECD countries between 1971 and 2010. They estimate that the elasticity in developing countries is 0.631 (standard error = 0.167) and in developed countries -0.181 (0.343).

I was curious why these results are very different from those in our stylized facts paper where we find a stable monotonic relationship between energy use and PPP GDP per capita over the 1971-2010 period for 99 countries (75 non-OECD, 24 OECD) with an elasticity of around 0.70. Obviously, Jakob et al.'s method is different, their sample is smaller, and they also use market exchange rates. So, I re-estimated their model using our dataset. I find that the elasticity in developing countries is 0.395 (0.081) and in OECD countries 0.479 (0.078). This is in line with our stylized facts results. The numbers are lower probably due to using differences and country and time fixed effects.

In supplementary material, Jakob et al. report that when they use PPP GDP data from the World Development Indicators the elasticity estimates are 0.626 (0.180) and -0.353 (0.474) for non-OECD and OECD countries respectively. I would have doubted that the differences are mostly due to the different source of PPP data  - we used the Penn World Table - but our OECD sample only includes three countries omitted by Jakob et al. So, this will need further investigation.


Jakob, M., M. Haller, and R. Marschinski (2012). “Will History Repeat Itself? Economic Convergence and Convergence in Energy Use Patterns.” Energy Economics 34: 95–104.

Thursday, August 14, 2014

Revenue-Neutral Carbon Tax with Global Temperature Indexation

The Climate Colab at MIT is running a competition for innovative climate policy proposals. Richard Hobbs is a local contender in this competition. You can support his proposal or make comments here. The winner will get to fly to MIT to present their proposal to US politicians, policy makers, economists, business executives and NGOs. Richard's proposal is a revenue-neutral carbon tax meant as a policy platform for the Republicans to bring forward to the next US election. It is revenue-neutral (cutting capital gains taxes and corporate taxes) and it is temperature indexed (so if climate sceptics are right the price trends to a low level).

Monday, August 4, 2014

Online Accessibility of Scholarly Literature, and Academic Innovation

Kevin Staub presented this paper today at ANU. They download data on all papers in fifty core economics journals over the decades of the 1990s and 2000s during which academic journals gradually went online. They test the effect of the fraction of references cited in article being online on the diversity of references cited. Diversity is measured by the average citation difference between articles in the reference list. Imagine I write an article and in the reference list I cite this paper by Kevin Staub and Martin Weitzman's article on recombinant growth cited by Staub then the distance between those two articles is 1. If I also cite Paul Romer's article "The Origins of Endogenous Growth" cited by Weitzman then the distance between Staub's paper and Romer's is 2 and between Weitzman and Romer is 1. Controlling for time and journal fixed effects and some other control variables they found that there were significant increases in the share of references with distances of 3 or greater the more of the reference list was available online. This seems expected to me as people find it easier to search for literature beyond the reference lists or even the forward citations of articles they have already seen as more of the literature is searchable online.

But the paper contains another result which I found much less expected and much more interesting that I think deserves a paper of its own. They found that papers with higher average distances between items on their reference lists received higher numbers of citations 20, 30, or 40 years down the track than papers with less diverse reference lists. So, this supports the notion that papers that bring together articles that were not previously cited together are more innovative. One might expect papers with more eclectic references to be produced by less professional more dilettantish authors. Of course, these papers were all published in the fifty core economics journals, so that probably acts to filter out the more outlandish papers or papers written by "outsiders" that are doomed to be ignored.

Frank Jotzo Responds to Danny Price

Frank has an op ed in today's Australian Financial Review - responding to Danny Price's op-ed last Wednesday which I also commented on, on this blog, last week. Here is a non-paywalled version of Frank's op-ed.

Sunday, August 3, 2014

Follow Me on Twitter

I'm planning on tweeting all my blogposts from now on, so you can follow me on Twitter. My username is sterndavidi. I've had a Twitter account since 2009 but never really used it much until now.

Friday, August 1, 2014

New ANU Open Access Policy

ANU researchers are now required to submit all published research outputs to our institutional open access repository. Details of the policy are here. Material should be submitted here. Previously, this was on a voluntary basis. Holders of ARC grants would have needed to justify why outputs of their project were not available on an open access basis. As in economics we have a very strong working paper culture this seems unnecessary. But that isn't the case in other disciplines and I guess a one size fits all policy is easier to implement and enforce.

Thursday, July 31, 2014

Direct Action vs. Carbon Pricing

There was an op-ed in yesterday's Australian Financial Review by Danny Price criticising the 59 economists including me who agreed to sign a statement in favour of carbon pricing and praising direct action. First, a clarification. By signing that statement we were not endorsing the previous Labor government's Emissions Trading Scheme. We were simply endorsing some pricing mechanism on carbon. Price criticises carbon pricing because of the "cost to the broader economy of any tax". Here he seems to be referring to the tax interaction effect. Where there are existing distorting taxes,  a new tax interacts with these and increases the costs of the new tax beyond the amount of the direct costs involved with abating pollution. The advantage of a carbon tax is that the revenue from the tax can allow the government to cut existing distorting taxes and reduce of offset this effect. This is known as a "green tax reform" and was much discussed in the so-called "double dividend debate". But imposing a regulatory cap on emissions (and issuing free tradeable permits) results in the same increased costs in the presence of existing distortionary taxes. So, this is why economists generally recommend auctioning emissions trading permits rather than giving them away.* This raises revenue allowing other distortionary taxes to be cut. Direct action is effectively a cap on emissions where the government subsidizes firms reducing emissions through a reverse auction. But this uses government revenue and doesn't allow the cutting of other taxes unless the government budget is cut drastically, which doesn't look like happening. If other spending isn't cut at all then the government will have to increase the existing distortionary taxes. So, direct action is worse than a carbon tax or traded permits on this basis. However, Price says that under direct action the government only imposes one dollar of costs on the economy for every dollar spent. This seems to be incorrect.

On top of that are the problems of the incentives for firms to inflate the baseline from which they claim they will reduce emissions.

So, I'm still in favor of carbon pricing of some sort though I think there are also important problems with emissions trading schemes that only provide a very volatile short-term price signal. The article by Ottmar Edenhofer in the latest issue of Nature Climate Change discusses some of these issues.

* I've argued that the Australian scheme failed because due to objections by the Greens, not enough free permits were given away allowing the scheme to be characterised as a "huge tax". The Australian scheme was less generous than the European scheme. But any such giveaway should be a transitory policy that would be replaced by more auctioning of permits over time.

Wednesday, July 30, 2014

Environmental and Resource Economics Journals

There aren't that many field journals in environmental, resource, and energy economics in the Journal Citation Reports:

REEP and JEEM are clearly the top journals in terms of article influence scores but Ecological Economics dominates the field as measured by Eigenfactor Score or total citations because it is a much bigger journal. JEEM is also ranked 48th among economics journals by Article Influence, so this whole field is not that highly ranked.

2013 JCR Released

The 2013 edition of Journal Citation Reports has been released. I don't like the new interface that was recently introduced and it wasn't obvious how to download data easily but then I discovered there was a button at top right to download everything you had results on at that point without selecting journals individually. So, now I figured that there will be more analysis coming. Anyway, here is the report for PLoS ONE, which is the journal visitors to my blog seem most interested in :)

Yes, the journal lost ground again on all impact metrics as has been expected. It still does fairly well for a journal that publishes so many papers. I have an article under review with submission number 40332 submitted on 16th July. So, using those numbers and last year's number of published articles we get an acceptance rate of 42%, which is likely to be an underestimate if the number of articles published is still rising.