My Climate Change Policy Assumptions and Expectations

Matthew Kahn posted a list of his working assumptions on climate change. I think it is really enlightening to see these laid out rather than just expressed implicitly. So I thought I'd list my ideas in response to each of Matt's points. In the following, Matt's points are in bold and mine in plain text.

1. I believe that global GHG emissions will continue to rise for decades. 

Technological change in non-carbon emitting energy technologies has been surprisingly fast despite climate policies having been relatively weak. This makes me optimistic that emissions will soon begin to fall. We used to talk about steeply rising emissions paths like RCP 8.5. In the most recent IPCC report, business as usual is now a fairly flat emissions path (not that we should put too much weight on consensus). On the other hand, I am pessimistic on energy intensity falling by as much as is assumed in many integrated assessment models (IAMs).  So, my expectation is for some fall in emissions or at least a flat path till 2050. I don't expect a steeply declining path because so much fossil fuel infrastructure continues to be built. My best guess is that we will somewhat overshoot the 2ºC target but in the later part of this century we will get really serious about carbon sequestration, which will eventually bringing the temperature down again. If we are lucky, impacts will remain fairly linear and we will avoid tipping points.

2. I do not take integrated assessment models of the impact of climate change seriously.

In general, I agree. On both the impact and technological change sides they are mostly just speculation, particularly on the impacts side. On the other hand, having some idea of how much we need to cut emissions at what cost is useful... and they can generate the social cost of carbon (see below). 

One of my standard assumptions is that technological change in terms of increasing technical efficiency of production will eventually end. It's likely that the level of technology will follow a big S shape curve from the Industrial Revolution on, and we are somewhere near the middle of the curve right now.

3. /4. Urbanization increases one’s income as one acquires more skill to succeed in the urban market. Private income growth fuels adaptation as people have more resources to protect themselves from the serious threats we now face.

Urbanization is part of the development process that increases energy use and to date carbon emissions but also provides some more adaptation capacity though it reduces other abilities to adapt. Density reduces the overall need for transport and for heating but increases the need for cooling. So overall I don't have a strong opinion on urbanization.

5. Due to market innovation, I believe that the Social Cost of Carbon (SCC) will actually decline over time.

The resource scarcity literature teaches us that the expectation that the efficient path of a price of a non-renewable resource is simply to grow at the discount rate as in the simplest Hotelling model isn't necessarily true. And if we solve the climate problem, then maybe the SCC will come back down again. I say "maybe" because though carbon in the atmosphere might be falling, we will have more to protect from impacts? In the long run, the carbon sink isn't a non-renewable resource. However, in the near term it seems reasonable to expect that the SCC is rising. Of course, the SCC is just an estimate, which is either generated by an IAM or depends on the same assumptions as an IAM. On the other hand, as long as we don't have an effective carbon price, we need a social cost of carbon number to put in cost benefit analyses.

6. The proper role of government here merits much more research. When do government efforts protect the poor versus when do government investments and rules create moral hazard and “Peltzman” effects such that we take on more risks such as moving to a risky area that the government has invested in sea walls to protect?

I think the government needs to take climate change into account when planning and adapting public infrastructure. And it has an important role in providing people information about climate change. But beyond that I don't see it has a role in adaptation. People bear the costs of adapting privately. I don't see a market failure there except due to information. So, I don't know why this should get specific attention rather than just be a side effect of general social welfare policy. Should we be building sea walls to protect land from flooding and is that a coordination problem? Well, I can't see how that can be anything but a short-term solution and so probably we shouldn't.

7. I am a fan and a producer of reduced form climate correlations. For example, over the last 4 decades how much lower has the growth rate of a nation’s per-capita income been during years when it very hot? These correlations are interesting. They play a “Paul Revere” role teaching us what future costs we could bear if we fail to adapt.

I am not a fan of this literature. I think it is more or less meaningless regarding climate change in general. If there is a one time hot year, you are not going to do long-term adaptation as Matthew points out. On the other hand, long-term impacts of climate change like sea level rise and species extinction won't happen due to one hot year. The literature can tell us something about what will happen if there are more of these exceptional years in the future but that's about it in my opinion.

Are the Benefits of Electrification Realized Only in the Long Run? Evidence from Rural India

 

I have a new working paper coauthored with my master's student Suryadeepto Nag on the impact of rural electrification in India. Surya did his master's at IISER in Pune with me as his supervisor. He visited Canberra over the last Southern Summer. This paper is based on part of Surya's thesis.

The effect of providing households with access to electricity has been a popular research topic. It's still not clear how large the benefits of such interventions are. Is electricity access an investment that generates growth? Or is it more of a consumption good that growing economies can afford? Researchers have used traditional econometric methods on secondary data (observational studies) and also carried out field experiments, such as randomized controlled trials (RCTs), to try to answer this question.

Experimental methods have generally found smaller and less statistically significant results than observational studies have. Is this because experiments are more rigorous? Or because observational studies usually measure impacts over a longer period of time? It's likely that it takes time for people to make use of a new electricity connection. They will need to save and buy appliances. Effects on children's education will take an especially long time to come to fruition.

We carry out a meta-analysis of 16 studies previously reviewed by Bayer et al. (2020):

We assigned each positive impact (for example on income or on education) found in a study the score of 1 and each negative impact a -1 and then averaged over all the impacts. The graph shows this "positiveness of impact" compared to the time households had been connected to electricity. While observational studies found more positive impacts than experimental studies, there is also a positive correlation between duration of connection and positiveness of impact (and between duration of connection and being an observational study). Regression analysis shows that only duration of connection is statistically significant. 

But this small sample of studies can't be that conclusive, so we then carry out our own analysis to test whether impacts increase over time.

Using three waves of Indian household surveys from 1994-95, 2004-5, and 2011-12, we quantify the impacts of short-term (0-7 years) and long-term (7-17 years) electricity access on rural household well-being. These surveys tracked the same households over time. We don't know exactly when a household was connected, just whether it was already connected in 1994-95 or whether it got connected between the other surveys. We do know when villages were connected.

We use a difference in differences regression that is weighted using "inverse propensity scores". This is supposed to compensate for the fact that households are not actually connected randomly to the grid. If, for example, poor households are less likely to get connected, we overweight them in the sample. In our main analysis, we exclude households that were already connected in 1994-95 so that the control group only includes households that were not connected by 2011-12.*

We find that long-term electricity access increases per capita consumption and education, and reduces the time spent by women on fuel collection (compared to the control group). The effect of short-term connection is smaller and statistically insignificant. We find no significant effects on agricultural income, agricultural land holding, and kerosene consumption. 

Here is our main table of results:

The long-term impact on consumption is really very big – 18 percentage points more than the control group over a 7 year period. The effect on education is 0.4 of a year relative to the control group.

We did some robustness tests – using different weights and including the households connected before 1994-95 as "very long-term connections". The results roughly hold up, though the weighting isn't ideal in either case.

We think our results show that experimental studies really need longer term follow-ups before coming to conclusions.

* The recent research on differences in differences shows that many past studies used inappropriate control groups.

China is pumping out carbon emissions as if COVID never happened. That’s bad news for the climate crisis

David Stern, Crawford School of Public Policy, Australian National University and Khalid Ahmed, Australian National University

Carbon emissions from China are growing faster now than before COVID-19 struck, data show, dashing hopes the pandemic may have put the world’s most polluting nation on a new emissions trajectory.

We compared emissions in China over the first four months of 2019 – before the pandemic – and 2023. Emissions rose 10% between the two periods, despite the pandemic and China’s faltering economic recovery. Power generation and industry are driving the increase.

Under the Paris Agreement, China has pledged to ensure carbon emissions peak by 2030 and reach net zero emissions by 2060. Our analysis suggests China may struggle to reach these ambitious goals.

Many believed the economic recovery from COVID would steer global development towards a less carbon-intensive footing. But China’s new path seems to be less sustainable than before. That’s bad news for global efforts to tackle climate change.

 

China has pledged to ensure carbon emissions peak by 2030 – but it’s heading in the opposite direction. Olivia Zhang/AP

An alarming trend in emissions

The COVID pandemic curbed greenhouse gas emissions in 2020, largely due to a drop in passenger travel. This led to hopes of a “green” economic recovery in which government stimulus spending would be invested into climate-friendly projects, to ensure a longer-term slowing of growth in emissions.

Some researchers examined the trends in China’s emissions up to 2019 and predicted the nation’s emissions would peak by 2026. Others have said the peak will occur even earlier, in 2025.

But unfortunately, it seems those predictions were too optimistic.

We examined data from Carbon Monitor, which provides science-based estimates of daily CO₂ emissions across the world. We compared emissions data from January to April 2019 (which represents typical pre-pandemic conditions in China) with the corresponding months in 2023. This period followed the removal of most COVID-related restrictions in China – such as testing requirements and quarantine rules – which essentially restored the country’s economy to business-as-usual.

We found average daily carbon emissions increased substantially between the two periods. In the first four months of 2019, China’s transport, industry, energy and residential sectors together emitted an average 28.2 million tonnes of CO₂ a day. In the first four months of 2023, daily emissions from those sectors were an average 30.9 million tonnes.

Emissions from the residential and transport sectors didn’t change much. This is mildly good news – it’s better than emissions going up. But these are the two smallest sectors, together accounting for only 18% of China’s emissions.

Rather, the increase was driven by emissions from China’s industrial and energy sectors. Average daily emissions from industry rose between 2019 and 2023 by 1.1 million tonnes or 11%. From energy, which includes electricity generation, they rose by 1.75 million tonnes or 14%.

Energy production from solar and wind in China did increase substantially between the two periods. But the growth was outweighed by electricity generated from fossil fuels.

Graph showing energy generation mix in China in the first four months of both 2019 and 2023. National Bureau of Statistics of China

Separate data show the growth of coal production in China has accelerated. In the two years prior to the pandemic, coal production variously fell or only grew slightly. But coal production grew during the pandemic, and this has continued. In the year to April 2023, coal production increased by about 5%.

While coal’s share of energy consumption fell substantially from 2007 to 2019, it has changed little since then. That’s mainly because energy use is growing fastest in the electricity sector, which remains dominated by coal.

The global picture

Emissions in many developed countries have fallen in recent years due to government policies, slow economic growth, and the shift from coal to natural gas.

Developing nations increasingly dominate global emissions. China might be expected to be a leader on the clean energy shift among developing countries – in part because it produces much less oil than it consumes. That means its energy supply is not secure, giving it an incentive to find alternative sources of power.

There’s another reason why China should be a trailblazer on emissions reduction. China is the world’s biggest emitter – so a percentage reduction in emissions there leads to far fewer tonnes of CO₂ in the atmosphere than if a smaller country reduced emissions by the same percentage. And, partly because China’s population and economy are so big, it stands to benefit more than any country in the world from a more stable global climate.

But as we’ve outlined, China’s trajectory is by no means world-leading. What’s more, moves by China on the international stage suggest it’s becoming less cooperative in climate negotiations than in recent years. We saw this at the COP27 global climate conference in Egypt late last year, when China did not join a pledge to curb methane emissions and refused to provide financial support to developing nations vulnerable to climate change.

The potential for cooperation on climate policy is being reduced further by ongoing tensions between China and the United States. All this serves to cast doubt on China following through on its Paris pledges – and certainly, on any chance its emissions will peak in the next two years.

David Stern, Professor, Crawford School of Public Policy, Australian National University and Khalid Ahmed, Visiting Fellow, Australian National University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Video from Arndt-Corden Seminar

Today, I gave a seminar in the Arndt-Corden Department of Economics Seminar Series, titled: "Electricity Markets with Speculative Storage and Stochastic Generation and Demand." We hope to post a working paper soon. In the meantime, here's the video * of my seminar: 

 * Introduction and question time deleted