Traditional Views, Revisionist Views, and Counter-revisionist Views on the Industrial Revolution

Following up on my post on our paper about the Industrial Revolution , I thought some more context would be useful. The traditional view of the Industrial Revolution was that the availability of resources of coal, iron ore, and earlier water power in Britain were crucial factors that lead to the Industrial Revolution occurring in Britain and not elsewhere. Of course, these weren't sufficient - industrialization didn't happen in China - and so institutions also seemed to be important. But in recent years economists have emphasized the role of institutions and downplayed the role of resources more and more. This is what I call the revisionist view. Tony Wrigley and Robert Allen are key exponents of a counter-revisionist view, reemphasizing the role of resources, though not ignoring the importance of institutions. Our paper is a mathematical and quantitative exploration of the counter-revisionist view.

Economists and historians are divided on the importance of coal in fueling the increase in the rate of economic growth in the Industrial Revolution. Many researchers (e.g. Wilkinson, 1973; Wrigley, 1988, 2010; Pomeranz, 2000; Krausmann et al., 2008; Allen, 2009, 2012; Barbier, 2011; Gutberlet, 2012; Kander et al., 2013; Fernihough and O’Rourke, 2014, Gars and Olovsson, 2015) argue that innovations in the use, and growth in the quantity consumed, of coal played a crucial role in driving the Industrial Revolution. By contrast, some economic historians (e.g. Clark and Jacks, 2007; Kunnas and Myllyntaus 2009) and economists (e.g. Madsen et al., 2010) either argue that it was not necessary to expand the use of modern energy carriers such as coal, or do not give coal a central role (e.g. Clark, 2014).

Wrigley (1988, 2010) stresses that the shift from an economy that relied on land resources to one based on fossil fuels is the essence of the Industrial Revolution and could explain the differential development of the Dutch and British economies. Both countries had the necessary institutions for the Industrial Revolution to occur but capital accumulation in the Netherlands faced a renewable energy resource constraint, while in Britain domestic coal mines in combination with steam engines, at first to pump water out of the mines and later for many other uses, provided a way out from the constraint. Early in the Industrial Revolution, the transport of coal had to be carried out using traditional energy carriers, for instance by horse carriages, and was very costly, but the adoption of coal-using steam engines for transport, reduced the costs of trade and the Industrial Revolution spread to other regions and countries.

Pomeranz (2001) makes a similar argument, but addresses the issue of the large historical divergence in economic growth rates between England and the Western World on the one hand and China and the rest of Asia on the other. He suggests that shallow coal-mines, close to urban centers together with the exploitation of land resources overseas were very important in the rise of England. “Ghost land”, used for the production of cotton for the British textile industry provided England with natural resources, and eased the constraints of the fixed supply of land. In this way, England could break the constraints of the organic economy (based on land production) and enter into modern economic growth.

Allen (2009) places energy innovation center-stage in his explanation of why the industrial revolution occurred in Britain. Like Wrigley and Pomeranz, he compares Britain to other advanced European economies of the time (the Netherlands and Belgium) and the advanced economy in the East: China. England stands out as an exception in two ways: coal was relatively cheap there and labor costs were higher than elsewhere. Therefore, it was profitable to substitute coal-fuelled machines for labor in Britain, even when these machines were inefficient and consumed large amounts of coal. In no other place on Earth did this make sense. Many technological innovations were required in order to use coal effectively in new applications ranging from domestic heating and cooking to iron smelting. These induced innovations sparked the Industrial Revolution. Continued innovation that improved energy efficiency and reductions in the cost of transporting coal eventually made coal-using technologies profitable in other countries too.

By contrast, Clark and Jacks (2007) argue that an industrial revolution could still have happened in a coal-less Britain with only "modest costs to the productivity growth of the economy" (68), because the value of coal was only a modest share of British GDP, and they argue that Britain's energy supply could have been greatly expanded, albeit at about twice the cost of coal, by importing wood from the Baltic. Madsen et al. (2010) find that, controlling for a number of innovation related variables, changes in coal production did not have a significant effect on labor productivity growth in Britain between 1700 and 1915. But as innovation was required to expand the use of coal this result could make sense even if the expansion of coal was essential for growth to proceed. Both Clark and Jacks (2007) and Madsen et al. (2010) do not allow for the dynamic effects of resource scarcity on the rate of innovation. Tepper and Borowiecki (2015) also find a relatively small direct role for coal but concede that: “coal contributed to structural change in the British economy” (231), which they find was the most important factor in raising the rate of economic growth. On the other hand, Fernihough and O’Rourke (2014) and Gutberlet (2012) use geographical analysis to show the importance of access to local coal in driving industrialization and urban population growth, though Kelly et al. (2015) provide contradictory evidence on this point. Finally, Kander and Stern (2014) econometrically estimate a model of the transition from biomass energy (mainly wood) to fossil fuel (mainly coal) in Sweden, which shows the importance of this transition in economic growth there.

Our new paper shows that the switch to coal in response to resource scarcity is a plausible explanation of how an increase in the rate of economic growth and a dramatic restructuring of the economy could be triggered in a country with a suitable environment for innovation and capital accumulation. We argue that in the absence of resource scarcity this shift might not have happened or have been much delayed.

References

Allen, Robert C. 2012. "The Shift to Coal and Implications for the Next Energy Transition." Energy Policy 50: 17-23.

Barbier, Edward .B. 2011. Scarcity and Frontiers: How Economies Have Developed Through Natural Resource Exploitation. Cambridge University Press: Cambridge and New York.

Clark, Gregory. 2014. “The Industrial Revolution.” In Handbook of Economic Growth, Vol 2A, edited by Philippe Aghion and Steven Durlauf, 217-62. Amsterdam: North Holland.

Clark, Gregory, and David Jacks. 2007. “Coal and the Industrial Revolution 1700-1869.” European Review of Economic History 11: 39–72.

Fernihough, Alan, and Kevin Hjortshøj O’Rourke. 2014. “Coal and the European Industrial Revolution.” NBER Working Paper 19802.

Kander, Astrid, Paolo Malanima, and Paul Warde. 2014. Power to the People – Energy and Economic Transformation of Europe over Four Centuries. Princeton, NJ: Princeton University Press.

Kander, Astrid, and David I. Stern. 2014. “Economic Growth and the Transition from Traditional to Modern Energy in Sweden.” Energy Economics 46: 56-65.

Kelly, Morgan, Joel Mokyr, and Cormac Ó Gráda. 2015. “Roots of the industrial revolution.” UCD Centre for Economic Research Working Paper WP2015/24.

Krausmann, Fridolin, Heinz Schandl, and Rolf Peter Sieferle. 2008. “Socio-Ecological Regime Transitions in Austria and the United Kingdom.” Ecological Economics 65: 187-201.

Madsen, Jakob B., James B. Ang, and Rajabrata Banerjee. 2010. “Four Centuries of British Economic Growth: the Roles of Technology and Population.” Journal of Economic Growth 15(4): 263-90.

O’Rourke, Kevin Hjortshøj, Ahmed S. Rahman and Alan M. Taylor. 2013. “Luddites, the Industrial Revolution, and the Demographic Transition.” Journal of Economic Growth 18: 373-409.

Pomeranz, Kenneth L. 2001. The Great Divergence: China, Europe and the Making of the Modern World Economy. Princeton, NJ: Princeton University Press.

Tepper, Alexander, and Karol J. Borowiecki. 2015. “Accounting for Breakout in Britain: The Industrial Revolution through a Malthusian Lens.” Journal of Macroeconomics 44: 219-33.

Wilkinson, Richard G. 1973. Poverty and Progress: An Ecological Model of Economic Development. London: Methuen.

Wrigley, E. Anthony. 1988. Continuity, Chance, and Change: The Character of the Industrial Revolution in England. Cambridge: Cambridge University Press.

Wrigley, E. Anthony. 2010. Energy and the English Industrial Revolution. Cambridge: Cambridge University Press.

From Wood to Coal: Directed Technical Change and the British Industrial Revolution

We have finally posted our long-promised paper on the Industrial Revolution as a CAMA Working Paper. This is the final paper from our ARC-funded DP12 project: "Energy Transitions: Past, Present and Future". The paper is coauthored with Jack Pezzey and Yingying Lu. We wrote our ARC proposal in 2011, but we "only" started work on the current model in late 2014 after I read Acemoglu's paper "Directed Technical Change" in detail on a flight back to Australia and figured out how to apply it to our case. We have presented the paper many times in seminars and conferences, though I will be presenting it again at the University of Sydney on April 6th.

The paper develops a directed technical change model of economic growth where there are two sectors of the economy each using a specific type of energy as well as machines and labor. The Malthus sector uses wood, which is only available in a fixed quantity per year, and the Solow sector uses coal, which is available at a fixed price. These assumptions are supported by the data. We don't think it is necessary to model coal as an explicitly non-renewable resource. As shallow deposits were worked out, technological change, including the development of the steam engine, allowed the exploitation of deeper deposits at more or less constant cost.

The names of the sectors come from the paper by Hansen and Prescott (2002): Malthus to Solow.  That paper assumes that technological change is exogenous and happens at a faster fixed rate in the Solow sector (which only uses labor and capital) than in the Malthus sector (which also uses a fixed quantity of land). The Solow sector is initially backward but because technical change is more rapid in that sector and it is not held back by fixed land, eventually it comes to dominate the economy in an industrial revolution.

Our paper updates this model for the 21st Century. In our model, technological change is endogenous, as is the speed with which it happens in each sector - the direction of technical change. We don't assume, a priori, that it is easier to find new ideas in the coal-using sector. In fact, we don't assume any differences between the sectors apart from the supply conditions of the two energy sources, which we explicitly model.

In most cases, an industrial revolution eventually happens. The most interesting case is when the elasticity of substitution between the outputs of the Malthus and Solow sector's is sufficiently high - based on our best guesses of the model parameters in Britain, greater than 2.9 - then it is possible if wood is relatively abundant for an economy to remain trapped forever in what we call Malthusian Sluggishness where growth is very low.* Population growth can push an economy out of this zone by raising the price of wood relative to coal and send the economy on a path to an industrial revolution.

These two phase diagrams show the two alternative paths an economy can take in the absence of population growth, depending on its initial endowment of knowledge and resources:

N is the ratio of knowledge in the Malthus sector (actually varieties of machines) to knowledge in the Solow sector. y is the ratio of output in the two sectors and e is the ratio of the price of wood to the price of coal. In the first diagram we see that an economy on an industrial revolution path first has rising wood prices relative to coal and also, initially, technical change is more rapid in the Malthus sector than in the Solow sector and so N rises too. In the long-run both these trends reverse and under Modern Economic Growth technical change is more rapid in the Solow sector and the relative price of wood falls. At the same time, we see in the second diagram that eventually the output of the Solow sector grows more rapidly than that of the Malthus sector so that y falls. The rate of economic growth also accelerates.

But an economy which starts out with a low relative wood price, e, or low relative knowledge in the Solow sector, N, can remain trapped with rising wood prices AND increasing specialization in the Malthus sector - rising y and N. Though there is coal lying underground, it is never exploited, even though switching to coal use would unleash more rapid economic growth in the long run. The myopic, but realistic, focus on near term profits from innovation discourages the required innovation in the Solow sector.

The core of the paper is a set of formal propositions laying out the logic of these findings but we also carry out simulations of the model calibrated to the British case over the period 1560-1900. Counterfactual simulations with more abundant wood, more expensive coal, more substitutability, less initial knowledge about using coal, or less population growth all delay the coming of the Industrial Revolution.

* We assume either that population is constant or treat its growth as exogenous.

Mid-Year Update

It's the first official day of winter today here in Australia, though it has felt wintry here in Canberra for about a week already. The 1st Semester finished last Friday and as I didn't teach I don't have any exams or papers to grade and the flow of admin stuff and meetings seems to have sharply declined. So, most of this week I can just dedicate to catching up and getting on with my research. It almost feels like I am on vacation :) Looking at my diary, the pace will begin to pick up again from next week.

I'm working on two main things this week. One is the Energy for Economic Growth Project that has now been funded by the UK Department for International Development. I mentioned our brainstorming meeting last July in Oxford in my 2015 Annual Report. I am the theme leader for Theme 1 in the first year of the project. In the middle of this month we have a virtual workshop for the theme to discuss the outlines for our proposed papers. I am coauthoring a survey paper with Paul Burke and Stephan Bruns on the macro-economic evidence as part of Theme 1. There are two other papers in the theme: one by Catherine Wolfram and Ted Miguel on the micro-economic evidence and one by Neil McCulloch on the binding constraints approach to the problem.

The other is my paper with Jack Pezzey on the Industrial Revolution, which we have presented at various conferences and seminars over the last couple of years. I'm ploughing through the math and tidying the presentation up. It's slow going but I think I can see the light at the end of the tunnel! This paper was supposed to be a key element in the ARC Discovery Projects grant that started in 2012.

In the meantime, work has started on our 2016 Discovery Projects grant. Zsuzsanna Csereklyei has now started work at Crawford as a research fellow funded by the grant. She has been scoping the potential sources of data for tracing the diffusion of energy efficient innovations and processing the first potential data source that we have identified. It is hard to find good data sources that are usable for our purpose.

There is a lot of change in the air at ANU as we have a new vice-chancellor on board since the beginning of the year and now a new director for the Crawford School has been appointed and will start later this year. We are also working out again how the various economics units at ANU relate to each other... I originally agreed to be director of the Crawford economic program for a year. That will certainly continue now to the end of this year. It's not clear whether I'll need to continue in the role longer than that.

Finally, here is a list of all papers published so far this year or now in press. I can't remember how many of them I mentioned on the blog, though I probably mentioned all on Twitter:

Bruns S. B. and D. I. Stern (in press) Research assessment using early citation information, Scientometrics. Working Paper Version | Blogpost

Stern D. I. and D. Zha (in press) Economic growth and particulate pollution concentrations in China, Environmental Economics and Policy Studies. Working Paper Version | Blogpost
 
Lu Y. and D. I. Stern (2016) Substitutability and the cost of climate mitigation policy, Environmental and Resource Economics. Working Paper Version | Blogpost

Sanchez L. F. and D. I. Stern (2016) Drivers of industrial and non-industrial greenhouse gas emissions, Ecological Economics 124, 17-24. Working Paper Version | Blogpost 1 | Blogpost 2

Costanza R., R. B. Howarth, I. Kubiszewski, S. Liu, C. Ma, G. Plumecocq, and D. I. Stern (2016) Influential publications in ecological economics revisited, Ecological Economics. Working Paper Version | Blogpost

Csereklyei Z., M. d. M. Rubio Varas, and D. I. Stern (2016) Energy and economic growth: The stylized facts, Energy Journal 37(2), 223-255. Working Paper Version | Blogpost

Halkos G. E., D. I. Stern, and N. G. Tzeremes (2016) Population, economic growth and regional environmental inefficiency: Evidence from U.S. states, Journal of Cleaner Production 112(5), 4288-4295. Blogpost

Long-run Estimates of Interfuel and Interfactor Elasticities

A new working paper coauthored with Chunbo Ma on estimating long-run elasticities. This is one of the major parts of our ARC DP12 project, the "Present" part of the title: "Energy Transitions: Past, Present, and Future". We just resubmitted the paper to a journal and I thought that was a good time to post a working paper with the benefit of some referee comments.

Both my meta-analysis of interfuel elasticities of substitution and Koetse et al.'s meta-analysis of the capital-energy elasticities of substitution show that elasticity estimates are dependent on the type of data – time series, panel, or cross-section – and the estimators used. Estimates that use time series data tend to be smallest in absolute value and those using cross-section data tend to be largest.

We review the econometric research that discusses how best to get long-run elasticity estimates from panel data. One suggestion is to use the between estimator, which is equivalent to an OLS regression on the average values over time for each country, firm etc. in the panel. Alternatively, Chirinko et al. (2011) argued in favor of estimating long-run elasticities of substitution using a long-run difference estimator, which is very similar to the "growth rates estimator" we have used recently.

We apply both these estimators to a Chinese dataset we have put together from both public and non-public data sources. We have data for 30 Chinese provinces over 11 years from 2000 to 2010. We estimate models for choice of fuels - interfuel substitution - and for the choice between capital, labor, and energy - interfactor substitution.

A big issue with the between estimator, which has made it relatively unpopular, is that it is particularly vulnerable to omitted variables bias. The big omitted variable in most production analysis is the state of technology. There is a lot of variation across provinces in productivity and prices and it seems that the two are correlated:

The first graph shows the price index for aggregate coal input that we constructed. Generally, coal is more expensive in Eastern China. The second graph shows an index of provincial total factor productivity, relative to Shanghai, which is the most productive province. Coastal provinces are the most productive - their distance to the technological frontier is low. To address this potential omitted variables bias, we add province level inefficiency and national technological change terms to the cost function equation. Chirinko et al. (2011) instead used instrumental variables estimation, but we found that their proposed instruments in many cases have very low or negative correlations with the targeted variables. We do use instrumental variables estimation, but this is due to the endogeneity inherent in our constructed coal and energy prices indices. We use Pindyck's (1979) approach to this. We also impose concavity on the cost function, if necessary.

The results show that demand for coal and electricity in China is very inelastic, while demand for diesel and gasoline is elastic. With the exception of gasoline and diesel, there are limited substitution possibilities among the fuels. Substitution possibilities are greater between energy and labor than between energy and capital. These results seem very intuitive to us. However, they are quite different to some previous studies for China, in particular the estimates in the paper by Hengyun Ma et al. (2008) Their estimates of the elasticities of substitution are negatively correlated with ours. Their study uses similar but older data, though we have improved the calculation of some variables. They use fixed effects estimation and don't impose concavity. These might be some of the reasons why our results differ. We also provide traditional fixed effects estimates with concavity imposed. These estimates are mostly close to zero. This suggests that the between and difference estimators are picking up longer-run behavior.

Which of these two estimators should we use in future? We can't give a definitive answer to that question but the difference estimator does seem to have some advantages. In particular, it allows cross-equation restrictions on the bias of technical change, which should result in better estimates of those parameters. So, that would be my first preference, though I am kind of reluctant to ignore the between variation in the data.

Wrapping up ARC DP12 Project

I just submitted the final report for this funded project which has been running since 2012 to the research office. We achieved most of the project goals despite receiving much less funding than requested. I also had to take on the role of research director for the Crawford School for 2 years of the project, which took up quite a lot of my time.

On the other hand, one of the main papers is still not quite complete and another is in the revise and resubmit stage. We haven't yet put out working papers for either of those papers either. So, the reduced funding and added admin work did slow things down. So far we have published the following papers that credit the ARC for funding:

Lu Y. and D. I. Stern (in press) Substitutability and the cost of climate mitigation policy, Environmental and Resource Economics. Working Paper Version | Blogpost

Csereklyei Z., M. d. M. Rubio Varas, and D. I. Stern (2016) Energy and economic growth: The stylized facts, Energy Journal 37(2), 223-255. Blogpost

Kander A. and D. I. Stern (2014) Economic growth and the transition from traditional to modern energy in Sweden, Energy Economics 46, 56-65. Working Paper Version | Audioslides | Blogpost

Bruns S. B., C. Gross, and D. I. Stern (2014) Is there really Granger causality between energy use and output? Energy Journal 35(4), 101-134. Working Paper Version | Blogpost

Stern D. I. and K. Enflo (2013) Causality between energy and output in the long-run, Energy Economics 39, 135-146. Working Paper Version | Blogpost

As we are still completing what I think is the most important paper of the project, on the industrial revolution in Britain, this story is definitely not complete yet. In retrospect, I probably should have asked for an extension of the project at the end of last year, so that we could put in a more complete final report to the ARC next year, rather than this year.

Two Papers Accepted for Publication

Two of our papers have just been accepted for publication. One is my paper with Yingying Lu on sensitivity analysis of climate policy computable general equilibrium models. It has been accepted for publication in Environmental and Resource Economics. The other is a paper with George Halkos and Nikalaos Tzeremes. The paper is on environmental efficiency across the U.S. States and has been accepted by the Journal of Cleaner Production. We haven't put out a working paper version of this one. I'll do a blogpost on it when it is available online at the journal. George was a lecturer at University of York when I was a post-doc there.

In the case of the first paper, we only sent it to one journal (JEEM) before the one it was finally published in. We sent the second paper to quite a few journals but managed to get it into one with a pretty high impact factor after significant revision.

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.

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.

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.

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 :)

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.

"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.

Ed Prescott to Speak at ANU

Ed Prescott (Nobel Laureate in Economics) will give the Trevor Swan Distinguished Lecture at ANU on 13th August. The lecture will be titled: Neoclassical Growth Theory: From Swan to Now. The blurb says:

"The Swan 1956 growth model is the cornerstone of secular growth theory. To broaden the model to encompass aggregate business cycle fluctuations Kydland and Prescott added an aggregate household to explain investment- savings and labor-leisure decisions. With this addition, neoclassical growth theory came into existence. Extensions of this theory have proven successful in the study of stock markets, growth miracles, prosperities and depressions, alternative tax policies, and differences in aggregate labor supply across countries and time. Deviations from the predictions of this theory are puzzles to be resolved and their resolutions have advanced neoclassical growth theory."

Unfortunately, I have to teach at that time, but I am hoping it will be recorded and some people will ask some good questions. Some of Prescott's work on growth is pretty fundamental to our current research on economic growth and economic history.

Malthusian Trap

Some interesting blogposts from Nick Szabo on the Malthusian trap and the breakout to economic growth. Follow the link in the post back to previous blogposts.

Energy and Economic Growth: The Animated GIF

It seems that everyone loves the animation of energy use per capita and GDP per capita that I am showing as part of my presentations on Energy and Economic Growth: The Stylized Facts. So, at James Hamilton's suggestion and with Zsuzsanna's help I have made an animated GIF of this slide sequence:

The graph is for the 99 countries that have data in both the Penn World Table (7.0) and the IEA Energy Balances. The line is the best fit log-log regression computed by Excel. As you can see the relationship between these two variables has been very stable over the last forty years globally.

World Energy Use Increased 2.3% in 2013

The annual BP Statistical Review was just released. It shows that world energy use increased by 2.3% in 2013. According to the IMF, the world economy grew 3% in 2013. World population is growing at about 1.1% p.a. Therefore, there was a 1.2% increase in per capita energy use for a 1.9% increase in GDP per capita - a ratio of 0.63 - which is a little below our stylized fact that energy use tends to increase by 0.7% for a 1% increase in GDP.

Energy and Economic Growth: The Stylized Facts

I contributed an article to the IAEE Energy Forum as part of their report on the New York City conference of IAEE. The topic of our paper that I will present in New York on 16th June is "Energy and Economic Growth: The Stylized Facts". The full paper is available as part of the conference proceedings. This has been a project under development for a while, being the subject of my "foundation seminar" (=inaugural lecture) here at Crawford School. Things progressed further once Zsuzsanna Cserekylei put a consistent dataset together for the 1971-2010 period and did the analysis. Then Mar Rubio contributed historical data and analysis. Anyway, this is the text of our article:

What overall patterns, or stylized facts, characterize the relationship between economic growth and energy use both across countries and over time? Energy economists and economic historians have investigated these issues, but existing research has either looked at how energy use and economic development vary across countries at one point in time or how they evolve over time in individual countries or groups of countries. Researchers have not linked together the cross-sectional and time series behaviors despite their obvious dependence on each other.

We investigate the links between the time and cross-sectional (or income per capita) dimensions using two datasets. One is a dataset for 99 countries from 1971 to 2010 that uses IEA and Penn World Table data. The other comprises historical data for the U.S. and a number of European and Latin American countries that extends back to 1800 for the U.S. and some Northern European countries and to later dates in the 19th and early 20th century for the other countries.

In recent years, economic historians, including one of the authors of this paper, Mar Rubio, have been working to reconstruct the energy history of many countries in Europe and the Americas for the years before the Second World War. Some of the historical data we use was prepared for the recently published Power to the People, authored by Astrid Kander, Paolo Malanima, and Paul Warde and published by Princeton University Press. Mar Rubio collaborated with Kander et al. on the Spanish data for that volume and led a team that developed historical data for Latin America. Though these data are obviously much more uncertain than those for recent years, they can provide insights into the long-run relationship between energy and economic development.

Our key finding from the recent data is that there has been a fairly stable relationship between countries’ GDP per capita measured in purchasing power parity adjusted Dollars and their per capita energy use over the last 40 years. A 1% increase in income per capita across countries is associated with a 0.7% increase in per capita energy use. This implies that energy intensity (energy use/GDP) is lower in richer countries and that on average a 1% increase in income per capita is associated with a 0.3% decrease in energy intensity.

The relationship is also stable in the sense that the average energy use per capita associated with any given level of income per capita has not changed over the four decades. This means that the typical country only managed to reduce its energy intensity by increasing its income per capita. A different way of looking at the same data is to compare countries’ average GDP per capita growth rate from 1971 to 2010 to the rate of change in their energy intensity over the same period. This relationship is shown in Figure 1:

The graph shows that higher rates of economic growth are associated with higher rates of decline in energy intensity. The graph also shows that if a country’s economic growth was zero then not only did its energy intensity not decline, but actually it increased on average.

Figure 1 also indicates that there are many countries where energy intensity rose despite economic growth. Our second main finding is that there was convergence in energy intensity over time and that the countries whose energy intensity rose typically had low energy intensity at the beginning of the period. Countries that were very energy intensive typically saw declines in energy intensity. There is now a tighter relationship between income and energy use than there was forty years ago.

In other words, though there has been some degree of “decoupling” of energy and growth in some formerly energy intensive economies, this has not been the common experience. Rather, there has been a homogenization, with countries increasingly resembling each other, while energy intensity globally has declined, but not by enough to reduce energy use.

This picture is borne out in the historical data too. Figure 2 shows the evolution of energy intensity and income over the last two centuries for four representative countries. Energy intensity appears to have declined the most in the United States, which was the most energy intensive economy in the 19th Century. On the other hand, energy intensity has been fairly stable in Spain, which was a very low energy intensity economy in the 19th Century. These time-paths are superimposed on the global distribution of energy intensity and income in 2010. This shows that in the past the United States was more energy intensive for its income level than any countries are today but that in the last few decades it has ceased to be remarkable in that way. On the other hand, the time paths of Sweden, Brazil, and Spain are mostly within the present day energy intensity distribution.

Our paper in the online proceedings also covers other regularities in the data. Specifically, there is some evidence that the share of energy in costs declines over time. But this “stylized fact” is still more of a prediction than a proven regularity. As is well known, the quality of energy increases over time and with income as countries have transitioned from traditional biomass, to fossil fuels, to primary electricity over time. We also find that the energy/capital ratio, which is an alternative to energy intensity as an indicator of overall energy efficiency, behaves somewhat similarly to energy intensity.

Future theoretical models of the relationship between energy use and economic development will need to take these stylized facts into account and make sure that their predictions match the facts. The stylized facts might also be useful for developing simple business as usual energy use scenarios.

The Relationship Between per Capita Energy Use and Income per Capita Has Been Very Stable

First preview of the paper that I will be presenting at the IAEE meeting in New York in a couple of weeks. Using Penn World Table 7 data for GDP per capita and IEA data for energy use, we (me, Zsuzsanna Csereklyei and Mar Rubio) found that the relationship between energy use per capita and income per capita has been very stable from 1971 to 2010 for a group of 99 countries. I've prepared an animation that shows this relationship. Just click through the pages in the pdf to see what happens as countries have grown (or not) over time.

RATS Command RESTRICT

I've spent the last couple of days trying to replicate results in RATS that Chunbo produced using STATA. In the process we found a lot of bugs in our data-processing and computer codes but now we can replicate each others results. We are estimating a translog cost share system together with the cost function. Previously, I have used the RATS command SUR to estimate a system of seemingly unrelated regressions and then the command RESTRICT(replace) to impose the restrictions and SUR(CREATE) to produce the restricted SUR estimates. This did not reproduce the same results as STATA at all. Instead using NLSYSTEM in RATS (despite the fact that the system is linear), I managed to reproduce the same results as STATA. This now seems to be the recommended way to do this type of analysis according to the RATS User Guide. So, I really don't know what the estimates produced by RESTRICT in RATS represent and I strongly recommend not to use them. This shows yet again that it is very important to know what the computer code you are using is actually doing.

Chunbo Ma Seminar at ANU

Chunbo Ma will be visiting ANU from Monday for a couple of weeks to work with me on our ARC project. On 10th April he is giving a seminar on his research on the effect of solar panels on house prices. Chunbo was my PhD student in the US and we have published a few papers together. Our current work is on substitutability in China. Well, it is really more about using new estimators to estimate elasticities of substitution and we will use Chinese data to do that. Please register and come along to Chunbo's seminar if you are in Canberra.

On 1st April I am giving a seminar at Arndt-Corden Department of Economics. It will be a longer version of the presentation I gave at the AARES meeting in Port Macquarie in February and at the recent AARES evening in Canberra. I just heard that the same paper has been accepted to the World Congress of Environmental and Resource Economics in Istanbul. Please come along to this seminar too!