ANZSEE Conference 2013

The 2013 ANZSEE Conference will take place in November at the Crawford School. All abstracts are due by 26th July. There will both be traditional papers and "working groups" that sound something like panel discussions. The last ANZSEE conference went to was the ANZSEE Conference in Darwin in 2009, which I thought was a great conference. The last ANZSEE or ISEE conference in Canberra was the 2000 ISEE Conference.

Stern and Enflo, Energy Economics

My paper with Kerstin Enflo: "Causality between energy and output in the long-run" has been accepted to be published in Energy Economics. In this case, the published paper will only differ slightly from the working paper version, which I have already blogged about. This is mainly because we only put up the working paper after getting a revise and resubmit from the journal. The question of when to post a working paper is something I have discussed on the blog and thought about quite a bit. We just got a revise and resubmit on this working paper. Our plan, is to add some additional analysis to answer the referees concerns. Even if we end up updating the database the final paper will not be radically different. There are other cases where we completely changed the dataset in response to referee comments. So, in that case, our first working paper was a bit premature.

Update...

I haven't blogged much recently as things have been very busy, teaching, admin, service (reviewing things), and lots of research projects in progress  - 5 papers in review or under revision and at least 12 at various stages from basic research to near completed - almost all my current papers now involve coauthorship. This is also the time of the semester when we also start preparing for the next semester's teaching. I'll be teaching my energy economics course for the second time. And I have been planning my travel over the winter break. First, I am going to Guelph to the workshop on econometric applications in climatology. It's all planned and they've posted my paper. I just need to write a presentation and go. Though I've been to Canada, all my visits so far have been to Quebec. I'll also visit a friend in Virginia. I'll be back here just in time for my students' exam and essay grading. Then I'll be off on another trip that will include Addis Ababa, where the 4th Lead Author meeting of the IPCC Working Group 3 will be held. It's in Addis because one of the co-chairs of the working group is from Ethiopia. Another is from Cuba. That would have been interesting too, but I suppose that no Americans would go to the meeting, which would kind of be a problem... I'll go to some other places too, which maybe I'll report on when I get back :)

Growth in a Time of Debt

A 2010 NBER working paper by Reinhart and Rogoff (also published in AER P&P) claimed that countries grow slower when they have high public debt to GDP ratios. Frank Jotzo pointed me to a blog which shows that there seem that the result is heavily influenced by a single year of -7.9% growth in New Zealand when the debt/GDP ratio was above 90% and there are also mistakes in the analysis. These issues are described in this new working paper. Without the New Zealand data point and correcting the mistake, the average growth rate in the 7 countries with debt ratios above 90% is 1.4% and with NZ is 0.3%. Still that is lower than the growth rate at the lower debt ratios and the highest growth rate is at the lowest debt ratio. Still, the negative correlation between debt to GDP ratio and growth rate does look real. But what is needed is probably a fixed effects regression of annual growth rates data on debt ratios or something like that. Also, Figure 2 in Reinhart and Rogoff presents medians as well as means of growth rates, which is more robust way of dealing with this data:

Table 1 in Reinhart and Rogoff shows data from a longer period and NZ now has positive growth at high debt ratios. Here the relationship looks more fragile though still hanging on. They also present similar data for developing countries where the relationship seems to be present too. So, while there are clearly problems with this paper I think the blog linked above is overly negative on the results. Reinhart and Rogoff have also responded to this criticism.

The real question though is about causality. Does high debt cause slow growth or vice versa?

The End of Economic Growth

A few months ago, there was a debate about whether economic growth was coming to an end. Based on this graph it looks like economic growth ends around 2060:

The downtrend in growth rate is fairly linear, but of course it is just wild speculation to project it forward several decades. Trends can change direction. This is based on Congressional Budget Office estimates of potential GDP growth. Also, this is total GDP, not GDP per capita. It is much less controversial to argue that population growth will come to an end this century.

Stochastic Trend Featured in List of Savvy Maths and Stats Websites

You can see the other sites featured by following this link. There are some that I occasionally visit like Andrew Gelman's site and a lot of the others look interesting too.

22 Year Citation Lag

I finally got a citation by someone other than myself to my first full length journal article, published in late 1990 just as I was starting my PhD! That's certainly an outlier in the citation distribution. The title of my "most failed journal article" now needs to pass to this one, which shows the importance of normalization.

Countries Where Crawford Faculty Got Their PhDs

This is just for faculty at level C (senior lecturer) and above. We have a lot of post-docs and junior faculty with ANU PhDs. If we include them, half our faculty have Australian PhDs. We only have 7 faculty (10%) with PhDs from Australian universities other than ANU.

Academic Rank vs. Citations

I updated an analysis I did a couple of years ago of Crawford faculty. It is a lot easier now to include citation data from Google Scholar as more than half our faculty now have profiles on Google Scholar. This chart shows the Google Scholar citations organized by academic rank. Level B is lecturer (equivalent to assistant prof in the US), Level C is senior lecturer (about equal to associate prof in the US), and D and E are associate professor and professor (both are probably equivalent to professor in the US). Though there are overlaps, it is possible to distinguish ranks quite clearly. If we controlled for discipline, the pattern would get even clearer. Economists have more citations than political scientists and perhaps environmental studies people have even more - Bob Costanza, of course, is the highest point on the chart.

ERA Verifies that Research Funding is Going to High Quality Research Groups

Yesterday I went to a presentation by the head of the Australian Research Council, Aidan Byrne. I asked him to comment on the article in the Australian that reported his thoughts that ERA results shouldn't be tied to larger amounts of funding. He said that ERA has already had significant effects without having money tied to it and the problem is that there aren't necessarily significant differences between being ranked a 3 or 4 or a 4 or 5 as scores are rounded up or down to produce the final outcomes. He said that the most valuable use of ERA is to verify that research funding is going to high quality research groups. There is a dramatic difference between the funding received by disciplines at institutions ranked 1 and 2 and those ranked 3,4, and 5 with a smaller difference between the latter three categories. Clearly the vast majority of funding is going to the groups ranked at world standard or above. It would help get this message across if ARC presented funding numbers per full-time-equivalent faculty member in each quality ranking. But they want to avoid doing productivity measures for some reason. The ARC slides I saw just show total dollars for all 5's, all 4's, and all 3's without adjusting for number of institutions or individual researchers. As there are usually fewer institutions ranked 5 this downplays the relationship between quality and funding. Also, it would make sense to then leave funding out as one of the indicators used to assess quality. And none of this information is in the ERA report. I think that would be valuable.

Is There Really Granger Causality between Energy Use and Output?

Finally, we have a revised version of the meta-analysis paper I presented in Perth in September out as a working paper.

So what's it all about? There is a massive literature on Granger causality testing of whether energy use causes economic growth or vice versa. We collected more than 400 papers. Yet the literature is very inconclusive. In fact we found that about 40% of tests for each direction of causation in our sample of 70 or so papers have statistically significant results at the 5% level. 40% is a lot more than 5% so either there must be a real effect or some kind of biases. On the other hand, it's not overwhelming evidence.

A recent paper conducted the first meta-analysis of this field of research. When we noticed this paper, we were initially worried that we had been "scooped". But, it turned out that the analysis in Chen et al. is fairly exploratory. Our paper tries to see if the effects found in the literature are genuine or simply the results of various biases. We do this by exploiting the "statistical power trace" - if an effect is non-zero then the test statistic associated with restricting it to zero should be greater in absolute value the greater the degrees of freedom associated with the model estimate. So we regress the test statistics for the Granger causality tests - after converting them all to normal test statistics - on the square root of the degrees of freedom. The way we have set things up, if we can reject the null that the regression coefficient on the square root of degrees of freedom is non-positive then there is a real Granger causality effect in the underlying literature.

We do this separately for tests of energy causes output and output causes energy. Overall there is no genuine effect in the literature but there do seem to be some genuine effects in subsets of the literature. Specifically, if we control for energy prices then income causes energy use. This is the energy demand function relationship, which Stern and Enflo also found was very strong in the Swedish data. Energy use might cause income but only if we control for employment and the VAR model passes a cointegration test. So, this is pretty tentative. There were some things we would have liked to test but simply had too little data. For example, does adjusting for energy quality make a difference?

There is a whole other story in the paper, which is about dealing with the econometric pitfalls associated with these kind of time series models. Initially, we found that the greater the degrees of freedom the more negative the test statistics were. Significantly so. It turns out that there is a tendency to included too many lags of the variables in small sample sizes. And these over-fitted models result in spurious rejections of the null hypothesis of no Granger causality. We control for this issue by including the number of degrees of freedom lost in fitting the model as an independent variable. This is likely to be important in other meta-analyses of Granger causality tests. We have a further econometric theory paper in preparation on this topic.

In some ways this is a silly question. We know that energy is used to produce things and we know that  in theory income is a determinant in the demand function for energy.  But observing that in the data in a consistent way doesn't seem to be that easy.

Australian Research Assessment Not Heading in UK Direction

That's the message I get from this interview with the head of the ARC, Aidan Byrne (formerly a science dean at ANU) in the Australian. The assumption of many in the sector, myself included is that the Australian research assessment exercise, ERA, and the funding attached to it would evolve in a way that generally followed UK practice with something of a time lag. In the UK, much more money is tied to the REF, the funding ratio associated with the three highest rankings of departments is 9:3:1, and case studies are being used very heavily to assess broader impact. Prof. Byrne argues that case studies should be used sparingly if at all to measure impact, not much money should be tied to ERA outcomes, and the funding ratio should be flatter. On Wednesday, I saw a presentation by Tim Cahill of the ARC on the ERA 2012 process and outcomes. One key finding was that for the citation based disciplines (most STEM disciplines (but not math or computer science) and psychology) there is a weak correlation between the ERA ranks assigned to universities and their citation performance relative to the benchmarks. A lot of subjectivity still seems to come into the ranking by the ERA committees. As they only count the number of citations per paper and not where they were cited, I guess that makes sense. So should Australian universities pay as much attention to ERA as they have been doing? For example, ANU has tied indicators in it strategic plan to the number of disciplines that achieve given ERA rankings by 2020. If I was the minister and looking for budget cuts would I want to continue with ERA on this basis?

Global Anthropogenic Sulfur Emissions Updated to 2011

A new article by Zbigniew Klimont, Steven Smith, and Janusz Cofala updates Smith et al.'s estimates of global sulfur emissions to 2011. The global downward trend that started around 1990 or earlier * continues. The small increase in the early part of the last decade was just a blip:

This chart also shows some previous estimates. In general the trend has been revised down over time. The trend in China is also now heading down:

Another paper by Smith and Bond declares "the end of the age of aerosols". Well not quite yet. We'll have to wait till 2100 for that :)

The downside for me of this new data is that I will now have to redo all the econometrics in a paper I have in preparation (with Robert Kaufmann) that was almost ready for submission :(


* As shown in my 2006 paper, studies prior to Smith et al. 2001 showed emissions continuing to grow strongly through 1990. Smith et al. (2001) showed a flattening of the trend in the 1980s. My paper showed a plateau from the mid-1970s to 1990 and Smith et al. (2011) showed a slow downward trend from 1973 to 1990 and then a steeper decline.

Saltwater vs. Freshwater

An interesting new working paper tries to define whether economics departments are "saltwater" or "freshwater" based on citation networks. They find that the divide is strongest for macroeconomics and econometrics. This makes sense as this divide is about macroeconomics. So, this seems to be a real thing. It's amusing to see where non-US departments fall on the gradient. Looking at places I've studied or worked, ANU is saltwater and Hebrew University is freshwater, which is amusing (there isn't much water at all in Jerusalem and ANU is located next to a lake). LSE is very salty.  More widely, Tel Aviv U. is very freshwater and Cambridge is very saltwater. By comparison, ANU and Hebrew U. are brackish. So it doesn't have anything to do with the water really :)

Lake Burley Griffin - ANU Campus is at lower left

February 2013 Crawford Research News

The latest research news is out, full of information about Crawford publications, working papers, and more.

More on Fusion

I've got a bit of feedback on the item on Lockheed Martin's fusion research. Apparently this is an improved version of the inertial electrostatic confinement technology. Also, apparently this is an active area of research with several research groups looking at it. Including at the University of Sydney.

Crows are Also Averse to Inequality

First evidence in non-mammals of inequality aversion.

Lockheed Promises Commercial Fusion Reactors in Ten Years

This news is on the face of it really exciting. But I can remember being very excited in 1989 about cold fusion. I would think a corporation would be more careful about what they announce than a couple of academic researchers, but you never know. I sent this to a person in the fusion area here at ANU and he said he thought it was pretty exciting too. That actually surprised me, though he is positive on the economics of fusion power, something I was quite skeptical about based on this kind of analysis. Fusion does seem to be technically feasible. The real question is it economically feasible relative to other non-carbon energy technologies.

WG3 SOD Review Opens Soon!

Registration for expert review of the Second Order Draft of Working Group III's contribution to the 5th Assessment opens on 25th February. We will be discussing these comments at the fourth and final lead authors' meeting in July in Addis Ababa.

Australian-German Climate College

Looks like we have a new competitor in Melbourne and... Berlin. Based on the PhD topics available it's stronger on the climate science and less on the economics and policy than what we can offer in Crawford. We also tend not to prescribe topics to this degree.

International Happiness

Just read the survey by Oswald and Blanchflower on the happiness literature. Something that surprised me was that there was very little discussion of the effects of culture on how people respond to surveys. It was mentioned but I thought it would be more important than this. I notice that as someone originally from England that I am much less willing to award high scores on surveys of say hotels or movies or whatever than Americans are and probably this also translates into how I would report on my happiness compared to people from some other cultures. Or is this not really important?

The paper does mention eating fruits and vegetables as being important for well-being. This is investigated in more depth in another of the authors' papers. I wonder if that helps explain why everyone seems to be so miserable in Eastern Europe in all these surveys? :)

Five New Open Access Economics Journals

Springer and IZA launch five new open access economics journals in the labor economics area. For the moment, at least, the journals are free to publish in too. Hopefully, these won't go the way of the BE Press journals which started out as open access journals and are now difficult to access paywalled journals. Given that they are published by Springer, I don't think so. The worst that is likely to happen is that authors will have to pay to publish in them in the future and/or the journals will close some day but still be hosted on Springer's platform.

Chinese State Council Endorses Cap on Total Energy Use

In 2011 I discussed China potentially setting a total energy use cap of 4 billion tonnes of "coal equivalent" by 2015. This target was not, however, in the end included in the 5 year plan. But it seems that the State Council has now endorsed that target. This is really a quite radical target of about 2 tonnes of oil equivalent per capita. All developed countries use more energy per capita than this. The stylised fact is that energy use increases with income though energy intensity declines over time. It remains to be seen how China will attempt to achieve this target and if they try whether they can succeed. I'm more skeptical of this than of their energy intensity and emissions intensity targets.

How Should Benefits and Costs Be Discounted in an Intergenerational Context?

I can see that this paper is going to be important. A paper by Arrow and twelve other authors reporting on a workshop at RFF in 2011 where the EPA asked 12 of the economists how the benefits and costs of regulations should be discounted for projects that affect future generations. This sounds similar to the panel convened in the early 1990s by NOAA on the consensus on contingent valuation that also included Arrow.

The economists all agreed that the Ramsey formula provides a useful framework for thinking about intergenerational discounting. However, they did not agree as to how the parameters of the Ramsey formula might be determined empirically. It seems that they also agree that declining discount rates make more sense than using different rates for projects with different time scales, stating: "Theory provides compelling arguments for a declining certainty-equivalent discount rate." But they think that doing this in the Ramsey framework involves too much uncertainty about parameter values. Therefore, they recommend the approach introduced by Weitzman in "Gamma Discounting". A declining discount rate raises, however, the issue of time inconsistency. They argue that as the discount rate schedule needs to be updated from time to time as new information is available, this updating means that a new decision will need to be made anyway and, therefore, there is no inconsistency. But I think they realise that this is a bit of a stretch.

I've always favored combining sustainability constraints combined with regular discounting to get around these issues. To my mind, anyway, doing a cost-benefit analysis of an issue involving very large changes like global climate change doesn't make economic sense nor moral sense. The problem is better stated as how to stay within the 2 Celsius target (or how to get back within it) at minimum cost (and equitably). And uncertainty should be modeled explicitly rather than built into the discount rate.

IAEE 2013

There are only a few days left to submit a paper to IAEE 2013. It overlaps with IEW 2013 so you can't got to both. I would love to visit Korea again though and the IAEE meeting in Perth last year was pretty good. But even if my abstract isn't accepted at IEW, I still want to go to Europe so I think I'll drop the idea of going to Korea.

Sage Open Drops Publication Fee to $99

As part of what seems to be a race to the bottom in publication fees for gold open access journals, Sage Open announced that it is cutting its publication fee to $99.

Sage Open aims to be the PLoS One of the social sciences and humanites and covers all those disciplines. There don't seem to be any economics articles on there. Not surprising, as the working paper culture in economics makes open access far less important than in many other disciplines.

Total Radiative Forcing if Black Carbon Effect is Three Times Greater

Following up on a couple of recent posts. This is what anthropogenic, natural and total forcing look like if radiative forcing from black carbon is three times stronger than the RCP project assumed:

This seems to fit the observed temperature record better.

Monash-UMelb-ANU Economics Paper in Science

Paper by Lisa Cameron and Lata Gangadharan of Monash, Nisvan Erkal of U. Melbourne, and Xin Meng of ANU on the effects of the one child policy on social behavior in China. They used economic experiments and sophisticated econometrics to see the effects of the one-child policy on things like trust and risk-taking. This seems to be part of a trend to more regular articles in Science on social science topics.

Anthropogenic and Natural Forcing and Slowing Temperature Increase

The figure shows the total anthropogenic and natural radiative forcing and their sum. Anthropogenic forcing includes greenhouse gases and black carbon aerosols that have a warming effect and sulfate aerosols that have a cooling effect. Natural forcing is solar irradiance and sulfur aerosols emitted by large volcanic eruptions into the stratosphere. It is assumed that carbon dioxide, methane etc. are totally anthropogenic. This is of course not the case as atmospheric concentrations depend on the rate of removal of these gases and our results will show that the concentrations are endogenous. Based on these data anthropogenic forcing was very low until around 1970 after which it has increased monotonically. The forcing due to sulfur and black carbon aerosols is very uncertain. The estimated effect of sulfur is quite large here and that of black carbon is low compared to the most recent estimates. If sulfur has less cooling effect and black carbon more warming effect the increase in anthropogenic radiative forcing would be greater, especially in earlier years.

Natural forcings are dominated by large volcanic eruptions. In the last decade total forcing has been fairly constant due to a decline in natural forcing and something of slowing in the anthropogenic forcing. This might explain the relative hiatus in global temperature increase in this period (Hansen et al., 2013; Kaufmann et al., 2011). This chart shows global temperature and ocean heat content (upper 700m) over the same period:

But as the system has long lags, attributing changes in this way is probably more tempting than true.

Revised Estimates of Radiative Forcing Due To Black Carbon

A 232 page paper with 29 authors is in press at Journal  of  Geophysical  Research-­Atmospheres titled: "Bounding the  role of black  carbon in the climate system: A Scientific Assessment." The bottom line is that previous studies have underestimated the global warming effect (radiative forcing) of black carbon by about three times. With the authors' new much higher estimate it is second only to carbon dioxide in its positive contribution to radiative forcing. If this is true, I think it is good news as it means that the climate sensitivity due to greenhouse gases based on recent data is then probably less than previously thought. Projections from the RCP exercise, show black carbon emissions declining in the future.

The problem is that this effect is very uncertain both in terms of emissions and the radiative forcing effect. From p2 of the paper:

"Total global emissions of black carbon using bottom-­up inventory methods are 7500Gg yr-­1 in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models, and should be increased by a factor of almost three. After this scaling, the best estimate for the industrial-­era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71Wm-­2 with 90% uncertainty bounds of (+0.08, +1.27) Wm-­2."

A 95% confidence interval would stretch from roughly -0.04 to +1.38. In other words we can't reject the hypothesis that the effect is zero at the 5% significance level.

The lead author Tami Bond has a two page summary available.

Casuality between Energy and Output in the Long-Run

In my annual review post I promised to complete some papers in progress... so here is the second working paper for 2013. This is actually the revised version we are submitting after getting a revise and resubmit so the job was to revise rather than complete the paper. An earlier version of the paper is actually already online titled "From Correlation to Granger Causality". That was a version I prepared for a conference in 2011. This version is coauthored with Kerstin Enflo. Added to this version there are unit root tests with structural breaks and cointegration analysis using the Johansen procedure with and without structural breaks. Also all the test statistics have been recomputed and the discussion of Granger causality in general is reduced.

This is one of a couple of studies we are doing on energy-GDP causality. The other is a meta-analysis, the first paper of which will be coming soon. There is a huge literature on causality between energy use and economic output. There are literally hundreds of papers. Most studies use short time series, in which it is hard to come to strong conclusions about what is going on. And it would seem that a lot of the results are actually spurious as the true significance levels of the tests are much lower (i.e. bigger p value) than the researchers think. There are quite a few studies that use panel data - i.e. combine time series data for many countries - in order to get a bigger data set and higher statistical power. There is one published meta-analysis that combines the results of many studies and there is one published paper with a much longer time series. Our new paper also adopts the strategy of using a very long time series.

We use Swedish data from 1850 to 2000 on GDP, "gross output", capital, labor, energy, quality adjusted energy, energy prices, and oil prices. We show that Granger causality techniques are very sensitive to variable definition, choice of additional variables in the model, and sample periods. All of the following appear to make a finding that energy causes growth more likely: using multivariate models, defining variables to better reflect their theoretical definition, using larger samples, and including appropriate structural breaks. We find causality from energy to GDP using a multivariate model for the full sample period. But in data for just the last 50 years this finding is reversed.
It is possible that the relationship between energy and growth has changed over time. On the other hand, it seems likely to me that causality in fact runs both ways, but what is actually detected depends on the size of the shocks to the two variables in the sample observed. One thing that has changed is that the cost share of energy has declined over time. This means that the output elasticity of energy has declined and we would expect the effect of changes in energy use to, therefore, have less impact on output. These smaller effects are harder to detect especially as the sample size gets smaller and reduces statistical power. On the other hand, the effect of output on energy use shouldn't have declined.

The paradox of the energy-GDP relationship is that the more important that energy is in terms of being essential in production the less the quantity of energy used will change in response to price shocks. However, the inability to substitute for energy will cause demand for other inputs and goods and services to decline by more. So energy prices can have a bigger effect on the economy but the quantity of energy to GDP relationship is weaker. We do find that energy prices have a significant causal impact on both energy use and output both in the longer and shorter (more recent) sample.

Another finding is that allowing for structural breaks reduces the signfiicance level of the Toda-Yamamoto Granger causality tests but makes it easier to find cointegration in our VAR models. This is paradoxical as cointegration implies that there must be Granger causality in at least one direction.

Upcoming Conference Deadlines

I just submitted papers to EAERE 2013, which is in Toulouse and the International Energy Workshop, which is in Paris. Both in June. The deadline for both is 1st February. EAERE requires presenters to submit a full paper, while IEW says your chances of getting accepted are better if you do.

Historic High Temperature in Sydney Today

Temperature at Observatory Hill hit 45.8C at 2:55pm today. Previous record was from 1939. I remember my mother telling me how hot it was in the late 1930s in Sydney. She was 7 years old then. My father remembered the German hyperinflation when he was the same age. Seems like these events made similar impressions.

Temperature records at Observatory Hill date to 1859. It hit 41.6C in Canberra which is close to but not a record. Nowra also had a new record high.

Grad Student Classification

I guess this can apply to post-docs and assistant professors too :)

Genes as Instrumental Variables

So shopping trips can be intellectually stimulating if your partner is also a social scientist :) On a trip to Costco today I commented on what seemed to me a higher proportion of "nicely rounded" people than at other places in Canberra and we started "debating" about the causality. Then I wondered about what sort of instrumental variable could sort that out. Well obviously if we had a gene marker associated with being fat that would potentially be a perfect instrumental variable - it would be correlated with being fat but shouldn't affect going to Costco in any other way, you'd think... and would certainly not be caused by going to Costco. We then jokingly discussed some ways to get genetic information from people as well as their weight without their knowing. Unfortunately ethics rules would forbid any of these and you'd need to get people's agreement to participate :)

When we got home I did some research. A full genome sequence still costs close to $10k. There is some research along these lines out there. It seems that besides cost the biggest issue is the low correlation between any given gene and given phenotypes. Such instruments would be weak. So it seems that multiple indicators and or factor analysis is needed. But if these issues are overcome and the cost comes down further, I can see that this will be become a huge area in many areas of economics including health and education obviously.

ANU is Number One in the World...

On mean kilometres between collaborators on papers! On average our collaborators are 4,522km from us:

This is just one the rankings you can get from the Leiden Ranking of universities. They aim to be more transparent than other well-known rankings like the Shanghai Jiaotong or QS rankings. Another very interesting feature are confidence intervals obtained by boot-strapping.

ANU does not rank very well by more conventional measures of impact. The authors preferred ranking is by the PP top 10% indicator. This is the percentage of a university's publications that are in the top 10% most cited publications. It's not source normalized, however, so universities with strong biomedical research efforts will rank higher. ANU is ranked only 114th with 12.9%. But note that even the top school - MIT - only scores 25.2%. So there is not much variation across most of the 500 research universities.

Another ranking is by source normalized impact factor. This should take into account the differences between disciplines. ANU ranks 118th with an impact of 1.21. MIT has an impact of 2.17. So there is again little variation. Much less variation than among journals which have less variation than individual researchers, which have less variation than articles. I'm actually surprised how little variation there is across universities. Of course, all these are research oriented universities, but still.

Something missing from these ranking is the average number of articles per researcher. It's not possible to work this out from the Web Science in any accurate way. Based on the RePEc rankings Australian economists publish above average numbers of papers given their RePEc rank, but these are cited less. I suspect because of the distance of Australia from elsewhere, despite our high levels of international collaboration.

First International Workshop on Econometric Applications in Climatology

There is a Call for Papers for the First International Workshop on Econometric Applications in Climatology to be held at the University of Guelph, Canada June 5-7, 2013. The deadline is 28 February.

It is interesting that there is enough activity in this space to hold a conference. It has definitely been attracting more and more attention. We - Robert Kaufmann and I - were pioneers in this area starting with our paper in Nature in 1997. Despite the relative success of this first paper I didn't find it an easy field to make much headway in and gave up on that line of inquiry around 2005-6. Robert persevered with some success. I now actually have a new paper in preparation. I hoep to get round to finishing it later this month. Maybe I should submit it to this conference?

Uncertainty Measures for Economics Journal Impact Factors

I have a new working paper out - Uncertainty Measures for Economics Journal Impact Factors. A version of the paper will appear in the March issue of the Journal of Economic Literature together with a couple of other papers on publishing in economics - one by Daniel Hamermesh and the other by Stefano Della Vigna and David Card. Some of the most recent literature review was posted here. I first blogged on this topic early last year starting with calculating the confidence interval for the Journal of Economic Growth's two year impact factor. In the end I did this for all economics journals that had a five year impact factor in the Journal Citations Reports. All 230 of them. The following graph shows the confidence intervals:

I used a stock price chart in Excel to generate this graph! As you can see, the top two journals - Journal of Economic Literature (JEL) and Quarterly Journal of Economics (QJE)  - are in a distinct class on their own. There is also a tail of a few very weak journals. I wonder why these are included in the Web of Science which deliberately only includes journals with decent citation rates. For the vast majority of journals it is hard to tell what rank they should have given the impact factor for a single year anyway. Certainly, small changes in rank from year to year which journals like to publicize when they increase have little meaning. Journals with very wide confidence intervals are those that publish few articles or have very skewed citations. In particular, the Journal of Experimental Economics ranked 23rd had one star article with far more citations than any other in the journal. It still has a respectable impact factor (1.8) without that article.

Another way of presenting the data is in terms of the range of ranks that could be ascribed to each journal:

For this graph I used the secret method for producing box plots in Excel.The shaded boxes is the continuous range of ranks that are are not statistically significantly different to the estimated rank (black dot) at the 95% confidence level. The whiskers indicate the most extreme outlying journals that have statistically insignificantly different ranks. The graph only shows the analysis for a subsample of 30 journals, though I compared each of these journals against all 229 other journals to derive the box plot. It's clear from this how much uncertainty there is over the exact ranks of most journals. The impact factor is the mean number of citations each article published in the journal got. Instead we can look at the median:

As the number of citations received by an article must be an integer the medians must be either integers or be half way between two integers. As most articles don't get many citations that means that most medians are zero or one. On the basis of medians, huge swathes of journals have equal rank, though the different medians seem to be significantly different from each other. If you're wondering about the dot on the left, JEL has the highest impact factor but its median of 3 is only half that of the QJE's.

Does this mean that impact factors are meaningless? I don't think so, but don't sweat small differences in impact factors when deciding where to submit your next academic paper.

Signs of Fracking

For more around a decade methane concentrations in the atmosphere were pretty much constant from year to year. In the last few years they have begun to creep up again Is that the sign of the fracking boom? Some research finds that methane leakage from fracking is much greater than from traditional gas fields and supply networks. We estimated that gas supply was the smallest anthropogenic source and gas flaring had declined from its peak contribution:

Flaring might also be again increasing. Climate Progress posted this image of gas flaring in North Dakota: