Sunday, August 13, 2017

Interview with Western Cycles Blog




Alejandro Puerto is a 20 year old who lives in Cuba. He has written: "Western Cycles: United Kingdom" a book that covers the economic and political history of the UK from 1945 onwards. He maintains a website of the same name that showcases his writing. You can also follow him on Twitter. He asked me whether I would I would do an interview for his blog. Here it is:

When did you became interested in the energy and the environment on economics?

I was interested in the environment from an early age and so I studied geography, biology (and chemistry) in the last 2 years of high school in England (1981-3) and then went on to study geography at university (in Israel). I had to pick another field and initially chose business as something practical but quickly switched to economics. I then realised that economics could explain a lot of geography and environmental trends. It was only when I went to do my PhD starting in 1990 that the faculty at Boston University at the Center for Energy and Environmental Studies which was linked to the Geography Department there were really focused on the role of energy in the economy and environmental trends that I became interested in understanding the role of energy. So I got a PhD in geography officially but had quite a lot of economics training and over time drifted closer to economics, so now I am even director of the economics program at the Crawford School of Public Policy at ANU.

I think that my generation is more informed on climate change because of the work of people like you. Do you think the same? Describe us some of your research.

Well, I think it has just become a much bigger and obvious issue as the global temperature has increased. The awareness of what is happening has been driven by people in the natural sciences. I have done some research applying time series models used in macroeconomics to modelling the climate system and though our first paper was published in Nature in 1997 and we have been cited on that in IPCC reports it has largely been on the fringes of climate science. My view of that research is that it takes an entirely different approach to modelling the system than most climate scientists use (mostly they use big simulation models called GCMs) and finds similar results which strengthens their conclusions. Most of my research has been on the role of energy in economic growth and the effect of economic growth on emissions and concentrations of pollutants. The effect of energy on growth is much more complicated than many people think – it seems that energy is more important as growth driver in the past in the developed world – adding energy when you have little has more effect than when you already have a lot. On pollution I’ve argued that the idea of the environmental Kuznets curve – that as countries get richer eventually growth will actually be good for the environment and reduce pollution is either outright wrong or too simplified. Instead in fast growing countries like China, growth overwhelms efforts to reduce pollution, while in slower growing developed economies clean up can happen faster than growth.

The Paris Summit filled your expectations as an environmental economist?

It was probably better than expected give the lack of success in getting agreement before then. Countries pledges are too little to reach the goal of limiting warming to 2C and we will probably have to remove carbon from the atmosphere in a big way later in this Century. The real question is whether countries will actually fulfil their voluntary pledges. OTOH low-carbon technology is developing fast and that is a positive that is making achieving the goals looking more possible.

How dangerous would be the environmental policy of the United States under the Trump administration on climate change?

It will delay action, unclear how much effect it will really have. Encouraging the development of new technology is important and having the largest and leading economy not focused on that is a negative. The US can’t actually leave till late 2020 and Trump has left the door open to submitting a weaker INDC in the interim and claiming victory. The US will still be involved in UNFCCC talks etc.

What do you think about the emissions of developing countries as they become industrious?

Developing country emissions are now larger than developed country emissions. But there is a big difference between China which now has higher per capita emissions than the European Union and say India which has still very low per capita emissions. China needs to take action and has made a moderately strong pledge. We should expect much less from India say. India is, though, strongly encouraging renewables development. Hopefully, technology is advancing fast enough that the poorest countries will end up going down a lower carbon path anyway as fossil fuel technologies gradually phase out.

Since 2006 China has become the greatest global polluter and emissions still growing continuously. China has no plans for decrease these emissions until 2030. What do you think about the attitude of this country?

They say they will peak emissions by 2030. In terms of reduction in emissions intensity per dollar of GDP their goal is quite strong. In the last 3 years Chinese CO2 emissions have been constant. Some argue they are already peaking now. I am a bit more skeptical. We need to see a few more years. There are several reasons why China is pursuing a fairly strong climate policy including energy security, encouraging innovation and reducing local air pollution as well as realising that they can benefit a lot from reducing their own emissions because they are such a large part of the problem.

In the long term, which kind of renewable energy would be the first to think about? Solar? Wind?

Solar – it has a greater potential total resource and looks like eventually prices will be below wind. Wind of course is strong in places without much sunshine like the Atlantic Ocean off NW Europe. I’m concerned though about the environmental impact of lots of wind power. In the long-run I’m still hoping for fusion to work out :)

Tell us about one of your favorite posts published by you on Stochastic Trend.

I’ve done less blogging recently as I now use Twitter for short things. Most of the posts are excerpts from papers or discussions of new papers. The most popular blogpost this year with visitors is:

http://stochastictrend.blogspot.com.au/2017/03/from-wood-to-coal-directed-technical.html

Where I discuss our working paper on the role of coal in the Industrial Revolution. The research and writing of this paper took a very long time and I was really happy to be able to announce to the world that it was ready.

Do you drive an electric car?

No, I don’t have a driving licence. My wife drives and we have a car but it is a large petrol-engined car that is not very efficient. We don’t drive it much though. We’ve driven less than 30,000 km since buying it in 2007.

Have you ever visited Cuba? Are you interested? There are a lot of 1950s cars, but there are places with tropical nature.

No, I haven’t been to Cuba. The only place I’ve been in Latin America is Tijuana, Mexico. I’m not travelling that much recently as we now have a 1 1/2 year old child. But Cuba probably wouldn’t be high on my agenda. I travel mostly to either visit family or go to academic conferences and work with other researchers. The only time I flew somewhere outside the country I was living in just to go on vacation was when I flew from Ethiopia to Kenya. I was at an IPCC meeting in Ethiopia.

Thursday, July 27, 2017

Error in 2014 Energy Journal Paper

I hate looking at my published papers because there are often typos in them which I didn't catch at the proofs stage...This time my coauthor, Stephan Bruns, found one in our 2014 paper in the Energy Journal: "Is There Really Granger Causality Between Energy Use and Output?" In Table 1, which describes the details of the studies in our meta-analysis, the control variable labeled "energy production" should actually be labeled "energy price". Energy production would be a weird control variable...

After digging into our draft files, it turns out I changed "energy pr." to "E Prod." systematically in this table just before we resubmitted it to the journal. I also added a footnote: "E Prod.=Energy Production". I don't know why I did this. I would have thought I would have asked, Christian Gross, who made the original version of the table, before doing this, but I can't find any email to prove that...

Sunday, July 9, 2017

Robots, Artificial Intelligence, and the Future of Work


I think that robots/artificial intelligence and the future of work is a hugely important topic. This is a very active research field but it seems to me that people (some informed by this research but most without referring to the research) are rushing to one of two conclusions. The first of these conclusions is that up till now economic growth has resulted in rising wages and full employment and so it surely will in the future too. The other is that robots must mean structural unemployment and so the solution is to introduce universal basic income or some similar redistributive policy.

I don't think either is necessarily true. In the past, the elasticity of substitution between labor and capital seems to have been less than one - both inputs were essential in production. Also, the two inputs are q-complements - an increase in capital per worker results in an increase in the marginal product and, therefore, wage of a worker. But it's possible that now, or in the future, that the elasticity of substitution between labor and capital is or will be greater than unity so that labor is not an essential input. Or that there are techniques that are designed just to use machines. Acemoglu and Restrepo (2016) assume that as some low-skilled tasks become automated other new high-skilled tasks are introduced. But there may be limits to people's cognitive ability. Most people aren't intelligent enough to be engineers and scientists. And the people that are intelligent enough now, might be worse than artificial intelligences in the future.

The other premature conclusion is that, definitely things are different now, and robots will result in structural unemployment or immiserizing growth, so that government intervention is needed. Usually, universal basic income is mentioned. Sachs et al. (2015) argue immiserizing growth is possible. This is one of the better papers out there I think, but still the framework is quite limited. as technological change is exogenous. It is possible that there is some self-correcting mechanism similar to that in Acemoglu's (2003) paper on capital- and labor-augmenting technical change. In that model, capital-augmenting technical change is possible for a while, but it introduces forces that return the economy to a pure labor-augmenting technical change path. Another important question is whether people have a preference to have at least some of the goods and services they consume produced by humans. Sachs et al. assume that utility is a Cobb-Douglas function of automatable and non-automatable goods. That means that consumption of human made goods could become infinitesimally small in theory.

I think we need to consider a range of models as well as empirical evidence before we can say what kind of policy, if any, is needed.

I wanted to do research on this and started doing some research on this but concluded that it is not realistic given my limited time for research because of my administrative - I am still director of our International and Development Economics Program - and parenting roles and my existing research commitments. Twitter isn't the only reason that I haven't updated this blog in 2 1/2 months. Comparative advantage suggests to me that I remain focused on energy economics. However, I think that the Crawford School of Public Policy should be looking at these kind of issues, and I am trying to encourage that. This is going to be one of the key policy questions going forward I think.

Thursday, April 27, 2017

How Accurate are Projections of Energy Intensity?

A new short working paper about how accurate projections of future energy intensity are. It's an extension of comments I made at Energy Update 2016 here at the ANU.

Energy intensity is one of the four factors in the Kaya Identity, which is often used to understand changes in greenhouse gas emissions. It is one of the two most important factors together with the rate of economic growth. The 2014 IPCC Assessment Report shows that less than 5% of models included in the assessment project that energy intensity will decline slower than the historic rate under business as usual:*


Is this likely? In the paper, I evaluate the past performance of the projections implied by the World Energy Outlook (WEO) published annually (except in 1997) by the International Energy Agency (IEA). The following graph shows the average annual difference between the projected and actual rate of change in energy intensity in subsequent years** for each WEO since 1994:


Positive errors mean that energy intensity declined slower than projected in the following years while negative errors mean it declined faster. So, for example, the error of -0.4% for 2000 means that over the years 2001-2015, on average energy intensity declined by 0.4% a year faster than was projected in the 2000 WEO.

It turns out that these errors are strongly negatively correlated (r = -0.8) with the error in projecting the rate of economic growth, which IEA outsources. Csereklyei et al. (2016), similarly, find that reductions in energy intensity tend to only occur in countries with growing economies. If we divide and multiply the growth rate of energy intensity g(E/Y) by the growth rate of GDP g(Y) we get the following identity:

The first term on the right hand side can be seen as the elasticity of energy intensity with respect to GDP.*** The following graph plots the elasticity as projected and as subsequently realized for each WEO:


The two seem to have tracked each other quite well. But there is a complication. The 1994 to 96 WEOs only projected future energy use up to 2010. 2010 is the only recent year when global energy intensity actually increased. This end point reduces (in absolute value) the actual elasticities for these three WEOs. From 1998 on, the difference between the projected and actual rate of change in energy intensity is calculated up to 2015. But through the 2011 WEO, 2010 is one of the years in the projection period. From 2012, 2010 is no longer include in the projection period and there is a sharp step down in the actual elasticity over the projection period. I think that the elasticities for 2012-16 probably under-estimate the true long-run elasticities and that the relatively stable values from 1998-2011 are more representative of what the future elasticities will be over the full projection horizon to 2030 or 2040.

If that is the case, then the projected elasticity of -0.6 in the 2016 WEO probably over-estimates the the elasticity that will be realized in the long run. Why would this be the case?

Early WEOs largely modeled energy intensity trends based on historical trends. This is not the case for recent WEOs. Over time, the IEA has endogenized more variables in their model of the world energy system and included more and more explicit energy policies. It is likely that the model under-estimates the economy-wide rebound effect. It's also possible that energy efficiency policies are not implemented as effectively as expected.

As part of our ARC funded DP16 project, we hope to contribute to improving future projections of energy intensity by empirically estimating the economy-wide rebound effect.

* The light grey area indicates the projections between the 95th and 100th percentile of the range for the default scenario.
** The base year for each WEO is 2-3 years before the publication date. Therefore, we can already assess the 2015 and 2016 WEO's.
*** We can use the identity to decompose the projection errors:


Over time the contribution of errors in the projected growth rate has increased relative to the contribution from errors in the elasticity. But I think that if we revisit this experiment in 2030 we will find a larger contribution from errors in the elasticity for what are currently recent issues of the WEO.

P.S. 23 June 2017

The paper is now published in Climatic Change.

Sunday, April 2, 2017

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.

Wednesday, March 29, 2017

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.

Tuesday, March 28, 2017

Cohort Size and Cohort Age at Top US Economics Departments

I'm working on a new bibliometrics paper with Richard Tol. We are using Glenn Ellison's data set on economists at the top 50 U.S. economics departments as a testbed for our ideas. I had to compute the size of each year cohort for one of our calculations, and thought this graph of the number of economists at the 50 departments in each "academic age" year was interesting:


There isn't as sharp a post-tenure drop-off in numbers as you might expect, given the supposed strict tenure hurdle these departments impose. But as we can see the cohorts increase in size up to year 5, which might be explained by post-docs and other temporary appointments, or people even moving up the rankings after a few years at a lower ranked department. So, as a result, the tenure or out year would be spread over a few years too. On the other hand, as the data were collected in 2011, the Great Recession might also explain lower numbers for the first few years.

A post-retirement drop-off only really seems to occur after 39 years. The oldest person in the study by academic age was Arnold Harberger.

Thursday, March 23, 2017

Two New Working Papers

We have just posted two new working papers: Technology Choices in the U.S. Electricity Industry before and after Market Restructuring and An Analysis of the Costs of Energy Saving and CO2 Mitigation in Rural Households in China.

The first paper, coauthored with Zsuzsanna Csereklyei, is the first to emerge from our ARC funded DP16 project.  Our goal was to look at the factors associated with the adoption of more or less energy efficient electricity generating technologies using a detailed US dataset. For example, combined cycle gas turbines are more energy efficient than regular gas turbines and supercritical coal boilers are more efficient than subcritical. Things are complicated by the different roles that these technologies play in the electricity system. Because regular gas turbines are less energy efficient but have lower capital costs they are mainly used to provide peaking power, while combined cycle turbines contribute more to baseload. So comparing combined cycle gas to subcritical coal makes more sense as a test of how various factors affect the choice of energy efficiency than comparing the two types of gas turbine technologies.

Additionally, some US regions underwent electricity market reform where either just wholesale or both wholesale and retail markets were liberalized, while other regions have retained integrated regulated utilities, which are typically guaranteed a rate of return on capital. Unless regulators press utilities to adopt energy efficient technologies there is much less incentive under rate of return than under wholesale markets to do so.


The graph shows that following widespread market reform at the end of the 20th Century there was big boom in investment in the two main natural gas technologies. More recently renewables have played an increasing role and there was a revival of investment in coal up to 2012. These trends are also partly driven by the lagged (because investment takes time) effects of fuel prices:


We find that electricity market deregulation resulted in significant immediate investment in various natural gas technologies, and a reduction in coal investments. However, market deregulation impacted less negatively on high efficiency coal technologies. In states that adopted wholesale electricity markets, high natural gas prices resulted in more investment in coal and renewable technologies.

There is also evidence that market liberalization encouraged investments into more efficient technologies. High efficiency coal technologies were less negatively affected by market
liberalization than less efficient coal technologies. Market liberalization also resulted in increased investment into high efficiency combined cycle gas. In summary the effect of liberalization is most negative for the least efficient coal technology and most positive for the most efficient natural gas technology.

The second paper is based on a survey of households in rural China and assesses the potential for energy conservation and carbon emissions mitigation when energy saving technologies are not fully implemented. In reality, appliances do not always survive for their designed lifetime and households often continue to use other older technologies alongside the new ones. The effect is to raise the cost of reducing energy use and emissions by a given amount. The paper computes marginal abatement cost curves under full and partial implementation of the new technologies.


The graph shows the marginal abatement cost curve for rural households in Hebei Province, scaled up from the survey and our analysis. Full-Scenario is the curve with full implementation of new technologies and OII-Scenario is with actual partial implementation. This analysis does not take into account any potential rebound effect of energy efficiency improvements.

The first author, Weishi Zhang, is a PhD student at the Chinese University of Hong Kong. She contacted me last year about possibly visiting ANU, and I supported her application for a scholarship to fund the visit (which unfortunately she didn't get), because I thought her research was some of the more interesting research on Chinese energy use and pollution that I had seen. I helped write the paper (and responses to referees in our revise and resubmit).

Monday, March 13, 2017

March Update

Just realized that we are already in the third month of the year and I haven't posted anything here yet! Things have been very busy with both work and family, so there hasn't been time to put out the blogposts only indirectly related to my research that I used to do - instead I'll usually tweet something on those topics - and research-wise things have either been at the relatively early research stages or the final publication stages. But there will soon be some new working papers going up and some blogposts here discussing them!

On the research front, in January we were mainly focused on putting the final touches on our climate change paper in time for the deadline for the special issue of the Journal of Econometrics. My coauthors want to wait for some feedback before posting a working paper on that. Then in February my collaborators Stephan Bruns and Alessio Moneta visited Canberra to work with me on modeling the economy-wide rebound effect as part of our ARC DP16 project. I spent the first half of the month working hard on the topic to prepare for their visit. We made good progress but it will be at least a few months till we have a paper on the topic ready. So far, it seems robust that the rebound effect is big. Then since they left, I've been catching up.

Recently, Paul Burke said: "You've already got three papers accepted this year - are you going to keep that pace up? ;)" He'd been keeping better count than me! Our original paper on the growth rates approach to modeling emissions and economic growth was accepted at Environment and Development Economics. Two related papers were also accepted - at Journal of Bioeconomics and Climatic Change. I also have three revise and resubmits to be working on... though one of those came in 2016... I'll put out one or two of those as working papers when we resubmit them.