00:00 Welcome to session free on pollution,
00:02 chaired by Shami Glass,
00:03 senior director and,
00:04 uh,
00:05 senior advisor and director for development policy
00:07 in the office of our chief economist.
00:09 In the session,
00:10 our panelists will share research that offers a comprehensive look
00:14 at both the challenges and opportunities
00:16 in using market-based approaches to address
00:19 pollution and climate change,
00:21 while our discussion will provide expert commentary
00:23 and help synthesize the key takeaways.
00:25 So.
00:26 With that,
00:26 let me hand over to our chair
00:29 and ask whoever is
00:30 on their way to please take their seats and and come over.
00:33 Thank you.
00:35 All right.
00:38 Thank you,
00:38 Carolina,
00:39 and welcome everyone.
00:41 Um,
00:41 you know,
00:42 I hope a lot more of you join,
00:44 but those who have joined,
00:45 thank you very much.
00:46 Uh,
00:47 I'd like to welcome all of you to our session on pollution.
00:51 And
00:52 the title
00:53 of
00:54 the session is pollution,
00:56 because
00:57 when we started thinking about the session and designing it,
01:00 we were motivated by
01:02 Professor Michael Greenstone
01:05 and his 2024
01:07 AEA Distinguished Lecture,
01:09 which was on the economics of the global energy challenge.
01:14 And in that lecture,
01:16 Professor Greenstone
01:17 highlighted that the global energy challenge
01:21 is defined by 3 often conflicting goals
01:25 that all countries have,
01:27 and this has to do with getting cheap
01:30 and reliable energy,
01:32 having clean air,
01:34 and limiting the damages from climate change.
01:37 And
01:38 when it comes to energy use,
01:40 there's a close correlation
01:43 between energy use per capita
01:46 and rising incomes per capita.
01:49 In fact,
01:50 there is no country in the world that has become rich
01:53 without a dramatic increase in energy use.
01:57 And right now there are billions of
01:59 people in low-income economies and middle-income economies
02:02 whose aspirations for themselves
02:05 include the dramatic rise in energy consumption.
02:09 So here in America,
02:11 an average American
02:12 consumes 13,000 kilowatts per
02:17 hours of electricity per year.
02:19 But around the world,
02:20 there are about 3 billion people who live in countries
02:24 with per capita
02:25 electricity consumption,
02:27 less than 1500 kilowatt hours a year.
02:32 So rising energy use has been accompanied by pollution
02:36 and carbon emissions.
02:38 And while America now accounts for 14%
02:41 of global carbon emissions,
02:44 emissions in middle-income countries,
02:45 particularly
02:46 in India and China,
02:48 have been on the rise,
02:49 linked with their growing economies.
02:51 So here's the challenge.
02:53 A policy
02:55 that's telling middle income countries and low income countries
02:59 not to have a dramatic rise in energy use,
03:03 that is to not develop,
03:05 it's just a nonstarter.
03:07 It sounds a lot like what Indemit told us this morning,
03:11 the hypocritical statements
03:13 made by elites in advanced economies.
03:16 And for all these countries,
03:18 fossil fuels are predicted
03:20 to be the dominant source of energy through the middle of the 21st century.
03:26 However,
03:27 there's a case to be made for aggressive reductions of fossil fuel,
03:31 and that's the immediate health effects
03:34 from conventional pollutants.
03:36 And Michael Greenstone's research that Kosik's going to tell us about
03:40 shows that air pollution poses the greatest external threat
03:44 to human health,
03:46 with the average person
03:48 losing more than 2 years
03:50 of life expectancy.
03:52 This loss is comparable to that from tobacco smoking.
03:55 And much greater from alcoholism,
03:59 terrorism,
04:00 or war.
04:01 So if low and middle income countries
04:04 need to take steps to reduce conventional air pollution
04:08 from fossil fuels,
04:10 it also provides a shot in the arm
04:12 for searching for alternative sources of energy.
04:15 So we're going to have a real vibrant debate this afternoon.
04:20 Because
04:20 we're going to talk about energy,
04:21 we're going to talk about clean air,
04:23 and we're gonna talk about reducing emissions.
04:27 And we have an amazing lineup of speakers.
04:30 Jan Steckel is the chair for Climate and
04:32 Development Economics at the Brandenburg University of Technology
04:36 and associated with the Potsdam Institute for Climate Impact Research.
04:41 Barbara Haer is a senior fellow
04:43 at the Goldman School of Public Policy at UC Berkeley.
04:46 And
04:47 is the director of the Berkeley Carbon Trading Project
04:50 and Kaushik Deb.
04:51 He is the executive director of the Energy Policy Institute at
04:55 the University of Chicago and leads EPI's work in India.
04:59 And I'm very excited and delighted my colleague,
05:01 Carolyn Fisher,
05:03 who is the lead economist and research manager
05:05 for development economics at the World Bank.
05:08 So Jan,
05:09 Barbara,
05:09 and Kaushik will give us about
05:12 17 minutes each max
05:14 on their research,
05:15 and Carolyn will kick us off with a discussant.
05:18 As a discussant following that,
05:20 we'll have a panel,
05:21 but I'd love to hear your questions,
05:23 so be ready to come to those mics and prepare your questions now.
05:27 So Jan,
05:27 let's start with you.
05:28 Thank you.
05:34 Thank you very much for the kind introduction and also the invitation.
05:39 Um,
05:40 I'm going to talk
05:41 about the effectiveness of carbon pricing.
05:45 So,
05:45 while I'm in climate and development economics,
05:48 so this is
05:49 why I'm interested in carbon pricing.
05:52 And I actually would like to kind of
05:53 summarize what we know from the existing literature.
05:57 And then I would like to discuss a little bit what we can learn,
06:00 particularly for low and middle income countries.
06:03 So
06:04 if you ask an economist,
06:05 OK,
06:05 what shall we do like in terms of rising emissions,
06:08 etc.
06:08 then they probably will answer like,
06:10 OK,
06:11 yeah,
06:11 let's put a price on carbon.
06:13 This is basically the standard idea,
06:15 like it is over 100 years old.
06:18 And we consider it to be the number one instrument to curb
06:21 climate change,
06:23 and it is not only kind of an academic or ritual exercise,
06:28 it is also getting increasing attention
06:31 in
06:33 low and middle income countries.
06:34 So you see in this nice report that
06:36 the World Bank is publishing every year that like every year
06:39 you basically see some more spots in the global south here.
06:45 So,
06:46 but
06:47 I would like to argue in this talk that
06:50 kind of,
06:51 there are huge research and implementation gaps and like of those
06:55 schemes that have been implemented in low and middle income countries,
06:59 we see many schemes with very,
07:01 very low prices.
07:02 And this raises immediately a couple of questions.
07:06 I'm not promising that I'm going to answer all of them.
07:09 Because it will never actually fit in 17 minutes,
07:13 but I will try to still kind of offer some
07:17 thoughts on actually how we can think about this.
07:20 So the first question is,
07:21 is it actually effective given particular market environments?
07:24 Second is,
07:25 is carbon pricing actually the optimal
07:28 policy instrument given other market failures?
07:30 So
07:31 as climate economists we tend to kind of focus on,
07:34 yeah,
07:34 we need to basically bring down emissions,
07:36 but what if Actually,
07:38 there are not only co-benefits of climate policy,
07:41 but also other spillovers,
07:43 negative spillovers,
07:44 for example,
07:44 on increasing air pollution,
07:45 etc.
07:46 So I think we need to understand this better
07:48 to then also
07:49 kind of think of the optimal design of policies.
07:53 Third is,
07:53 of course,
07:54 the question,
07:54 why is it so difficult to implement?
07:56 And fourth,
07:57 is what would be kind of specific design features that can make it work also
08:02 in uh environments in low and middle income countries.
08:06 But I would like to actually in this talk focus on two questions.
08:10 One is
08:11 what do we actually know about the effectiveness of carbon pricing?
08:15 And the second is can we be sure that
08:18 this also applies for low and middle income countries?
08:20 And I would like to start with the first
08:23 kind of question.
08:24 With the paper that we have published last year,
08:27 which is actually a systematic review and meter analysis of
08:31 the expo elevation of the effectiveness of carbon pricing.
08:34 So
08:35 we are actually kind of looking into the literature that has in the causal setting,
08:40 looked into,
08:40 OK,
08:41 there has been some form of pricing instrument can be a tax,
08:44 can be a trading scheme.
08:45 What has actually happened to emissions.
08:48 And the reason why we
08:49 engaged in this endeavor was twofold.
08:51 First was,
08:53 well,
08:54 we're,
08:54 it's an interesting question.
08:56 But second is that basically it has been kind of,
08:59 there have been a couple of papers that came out,
09:01 like one,
09:02 for example,
09:02 by Jessicare 2020 in environmental research letters saying,
09:06 OK,
09:07 carbon pricing has not actually been effective.
09:10 And this was counterintuitive to us,
09:12 not only basically from kind of the theoretical
09:15 papers and knowledge that we have,
09:17 but also
09:18 based on the primary studies that partly we ourselves have actually conducted.
09:24 So,
09:24 and the,
09:25 the second dimension where we were puzzled was that basically what was kind
09:28 of labeled to be a systematic review was not at all systematic.
09:32 It had kind of quite a few gaps in terms.
09:34 So we,
09:34 we actually engaged in
09:37 doing a proper systematic review,
09:39 which kind of
09:40 Um,
09:41 means that we have to go through various steps.
09:44 So the first is
09:45 that we have to engage in systematic screening,
09:47 really trying to scrape all the relevant kind of uh literature databases,
09:52 including Scopus,
09:54 uh,
09:54 Redpack,
09:54 Google Scholar,
09:55 basically what have you.
09:57 And really kind of looking into with a with a
10:01 predefined set of keywords like carbon pricing,
10:04 emissions trading,
10:05 expost,
10:06 causal incidents,
10:08 etc.
10:08 etc.
10:09 uh,
10:10 kind of to make sure that we identify all kinds of the relevant literature.
10:15 So then,
10:16 basically,
10:17 uh,
10:18 we have developed some automated tools to make the sorting a little bit more,
10:22 um,
10:23 yeah.
10:23 Uh,
10:25 handy for us,
10:26 but still,
10:26 in the end,
10:27 there were about 4000 papers where we had to read the abstracts by hand,
10:31 always making sure that it's not only one person,
10:33 but at least 2 persons
10:35 to basically make sure that we don't miss anything.
10:37 So,
10:38 in the end,
10:38 we came up with a,
10:40 with a specific set of papers and literature facts that we kind of think
10:45 are
10:45 more or less comprehensive.
10:47 And as a second step,
10:49 then we had to engage and think,
10:50 OK,
10:51 how can we now extract
10:53 kind of the effects and the effect is we are interested in
10:58 is the reduction
11:00 of
11:01 carbon emissions after the introduction of a specific scheme.
11:05 And of course,
11:06 kind of the literature
11:07 gives all kinds of different methods,
11:09 different or
11:11 Um,
11:12 synthetic control,
11:13 etc.
11:14 so this had to be harmonized also this,
11:16 the literature,
11:16 the original papers look into different
11:19 kind of time frames,
11:19 etc.
11:20 but all of this basically we,
11:22 we try to harmonize and we came up
11:24 with a specific sample of
11:27 existing carbon price.
11:28 Schemes and ETS
11:30 that um
11:31 basically
11:32 uh have been covered in about 100 publications
11:36 and in those about 100 publications we identified
11:40 about 470
11:42 particular
11:43 uh treatment effects,
11:45 OK.
11:46 And you can see if you look closely into this table
11:49 that those schemes cover
11:51 like a very different um share of the emissions and also if you look into the prices,
11:58 they range from $3 in the red scheme
12:01 to about um
12:04 above $100 in
12:07 uh
12:08 in uh in Sweden.
12:10 So let's have a look into the results.
12:15 The results actually are
12:17 that
12:17 once we have seen carbon pricing schemes to be implemented,
12:21 they have on average reduced emissions significantly by about 10%.
12:26 So this is what the literature says.
12:29 And
12:30 you see that there are kind of huge
12:32 differences like ranging from about 20% in the reggie
12:35 to actually a positive effect in the Swiss ETS.
12:40 So we did some analysis aiming to try
12:44 to explain what is actually now the differences and
12:48 One of the largest differences is actually
12:50 the sectoral coverage.
12:52 So when it has been actually applied on energy or industry sectors,
12:57 um,
12:57 we we can find that actually the emission
13:00 reductions have been larger than in other sectors.
13:03 Also,
13:03 and this is kind of logical,
13:05 if the original kind of studies have looked into a longer period,
13:09 then we also find a larger reduction effect.
13:13 So you might wonder,
13:15 and I'm saying this up front because this question comes up
13:18 every time,
13:19 why has it actually been positive in Switzerland?
13:23 And this is actually the last point,
13:25 like the kind of how the study has been
13:28 conducted is also a decisive kind of predictor or like
13:32 element why these are different.
13:34 And in the,
13:35 in this particular study.
13:37 of
13:38 the authors looked into the difference between the introduction of the Swiss ETS,
13:42 which has replaced a different scheme,
13:44 the regulation in the industry sector,
13:46 which has been
13:47 actually more ambitious than the ETS.
13:50 So
13:50 it is not so surprising that we find
13:53 a positive effect.
13:55 But it's still kind of um relates to an important
14:00 question that we all know when we are in academia,
14:02 that kind of not every study is of its,
14:04 of,
14:05 of the same quality.
14:07 So what we also did is
14:09 That we wanted to know
14:11 what is actually
14:12 the effect of particular bias
14:15 and the effect of statistical power in those studies,
14:18 and I just realized that the numbers are I mistakenly swapped them.
14:23 So
14:23 when actually controlling for specific biases,
14:26 so for example the control groups are not comparable to
14:30 And the treatment groups or there are some omitted controls which we
14:34 more or less kind of did by hand,
14:37 so this coding,
14:39 then we find that OK,
14:40 this is actually not really affecting the results.
14:43 It is still 10.8%. However,
14:45 if you basically take those studies out that are statistically underpowered,
14:49 then we find a
14:51 slightly lower effect of about 7%.
14:53 But the bottom line remains the same,
14:56 so emission pricing.
14:58 Where we have robust kind of
15:00 ex post causal evidence has been effective
15:04 in negative like in bringing down emissions.
15:07 So one thing that you immediately realize when you look through
15:10 these kind of um uh set of schemes that have been studied
15:14 is that there's very little evidence on low and middle income countries.
15:19 And
15:20 I won't have time to actually go into this in detail,
15:23 but this is exactly what we're doing in my
15:25 lab that we try to provide this primary evidence.
15:28 And I just
15:29 kind of,
15:29 uh,
15:30 would like to
15:31 give a very,
15:32 very quick
15:33 insight on a study that has just been published
15:35 as a working paper by one of my postdocs,
15:38 Johannes Galli,
15:39 and they actually look into the effect of the South African carbon tax,
15:43 which has come
15:45 in effect in 2019 in the South African industry sector.
15:49 And they actually find that there is that they cannot prove
15:52 any robust evidence on emission reductions in this particular scheme.
15:58 Um,
15:59 but I would like to actually go one step further.
16:01 And this is why I decided to,
16:03 um,
16:04 actually introduce another paper.
16:06 I haven't been the co-author here,
16:08 but uh my colleagues at
16:10 at PI have actually published this last year in Science,
16:13 and they kind of ask the question the other way around,
16:16 right?
16:16 Like if we basically do policy evaluation,
16:19 then we often pick our favorite policy instruments,
16:22 emission pricing.
16:23 And then we do an evaluation,
16:24 has this been effective.
16:26 But actually the question that we're interested
16:28 in is what has brought down emissions?
16:31 And this needs a slightly kind of different research design.
16:34 And this is what they have been doing.
16:36 They have
16:37 developed basically a framework
16:39 where they for different countries and sectors,
16:42 look into how emissions have developed by a synthetic kind of control framework,
16:48 they kind of look into emission brakes.
16:50 And whenever they detect a significant emission break,
16:53 not just kind of a random 1% dip,
16:56 but like at least 5 to 10%,
16:59 they say,
16:59 OK,
16:59 this now actually is an emissions break in a particular sector.
17:03 When applying this,
17:05 they find
17:06 in overall 69 breaks.
17:09 With an average emission reduction of 19%.
17:12 You can see like all across the board,
17:15 like in Europe,
17:15 in North America,
17:16 Latin America,
17:18 Asia um Oceania,
17:20 so we have actually seen those breaks everywhere.
17:23 What they do next
17:25 is that they assign
17:27 specific policies
17:29 uh to those bricks.
17:30 So they actually use the database from the OCD on um
17:35 On,
17:35 on policies,
17:36 all kinds of policies,
17:37 not only price policies,
17:38 but also,
17:39 um,
17:40 changes in the building code,
17:41 for example,
17:42 or air pollution standards,
17:43 etc.
17:44 and they assign it to those brakes.
17:48 In the end they come up with this very complicated graph.
17:51 I don't expect you to understand it at all,
17:53 but basically it gives you kind of like all the
17:56 various kind of policies in countries where we have actually seen
18:00 some policy induced reduction.
18:03 If we just zoom in one example,
18:05 China for example.
18:07 So this has been a break detected in the industry sector.
18:11 And they can assign
18:12 kind of the pilot ETS in
18:15 in China
18:16 and the fossil fuel subsidy reform to this effect.
18:21 Doing this for many,
18:22 many countries,
18:23 they can then
18:25 also actually look into specific differences between
18:28 developed and developing countries by sector.
18:31 And I think this is really interesting to look at,
18:34 because
18:35 first result of this paper is that generally policy mixes
18:39 mixes have been much more effective than single policies.
18:43 And they have in particular been effective if there
18:46 has been some price instrument actually in place.
18:50 But there are some kind of differences.
18:52 So if you look into this graph,
18:53 the different kind of
18:55 circles here show you
18:56 kind of what kind of policy has been affected.
18:59 So for example,
19:00 here,
19:00 727.3% of the successful interventions were regulation alone,
19:05 but you see that most were actually combined with some subsidy with some pricing,
19:10 etc.
19:10 etc.
19:12 So what they find is when in those sectors
19:15 with private consumers,
19:17 they find the most complementarities if you like.
19:21 Then the pricing instruments have in particular been
19:24 affected and this is a quite similar effect,
19:26 as quite similar results to what we have found also in the systematic review,
19:31 like where we actually see profit maximizing firms at work
19:34 and this is true both in developed and developing economies.
19:38 They're basically pricing instruments have been in particular.
19:41 Um,
19:42 effective.
19:43 So now,
19:45 the most
19:46 interesting difference is in the electricity sector.
19:48 So you see in developed countries,
19:51 actually,
19:51 it's been mainly been pricing instruments that have
19:54 managed to bring down emissions in the electricity sector.
19:57 In developing countries,
19:59 they could not
20:00 find any.
20:02 Emission brake
20:03 that can be
20:04 traced back to pricing instruments alone.
20:06 It's only subsidies and it is regulation.
20:09 And this of course as a kind of immediately gets us to the question,
20:14 so what are the conditions for pricing
20:17 interventions come pricing to work successfully.
20:20 Like looking into the electricity sector of developing countries,
20:23 a couple of things come to mind.
20:25 It is the role of liberalized markets and
20:26 other price distortions that might be at play.
20:29 The role of specific,
20:30 you know,
20:30 sequences of policies,
20:32 for example,
20:32 the liberalization of an electricity market,
20:35 might need to come first before we apply a pricing instrument.
20:39 And then of course the role of institutions,
20:41 state capacity,
20:42 etc.
20:42 to regulate.
20:43 And
20:43 last but not least,
20:44 of course,
20:45 the role also of state owned enterprises that
20:47 might be particularly salient in the electricity sector.
20:52 So now I have another talk of 17 minutes,
20:55 uh,
20:56 what we can expect.
20:57 But and I won't give it to you,
20:59 but I just wanted to
21:01 mention a couple of things
21:03 uh for discussion.
21:05 So,
21:05 um,
21:06 why should it be different from,
21:08 from theory?
21:08 One is kind of the effectiveness,
21:10 and I think I have talked about this.
21:12 I would like to say two words more about the interaction with other externalities,
21:17 including health,
21:17 because we have been doing quite some work
21:20 to look into the effects of
21:23 Cooking fuels,
21:24 when actually people are exposed to price changes
21:27 by subsidy reform or by a carbon price.
21:30 And this is actually in the fact that in developed countries,
21:33 nobody would actually think of.
21:34 But in developing countries,
21:36 it is highly important because we want people to use more fossil fuels
21:39 in terms of EPG in terms of lowering exposure to indoor air pollution,
21:43 etc.
21:44 And we find
21:45 that this might actually counteract.
21:47 So the introduction of a carbon price might actually lead
21:51 to more indoor air pollution because people are pushed down
21:54 the energy ladder and actually use more firewood or charcoal,
21:58 etc.
21:58 with related health consequences.
22:00 And when thinking this through
22:02 and then looking actually into the comparison between social costs of carbon.
22:08 And these health costs
22:09 we find that in many countries including India
22:12 actually for the country itself I've seen you
22:16 um
22:17 um it would actually not be optimal to apply a car price.
22:21 So
22:22 then it comes to the last
22:24 point that I would like to make and this is
22:26 our countries actually because you could think of
22:29 design schemes right to alleviate this effect.
22:32 But the question is,
22:33 do countries have actually the
22:35 the institutional means to do that,
22:38 and
22:40 who would actually need to kind of be compensated?
22:43 Do we need to think of specific design features,
22:46 etc.
22:46 I think all of this
22:47 is highly relevant
22:49 when thinking about carbon pricing in
22:51 developing countries.
22:53 And with that,
22:54 I stop
22:55 and thank you very much.
23:00 Thanks so much,
23:01 Ian,
23:01 for those excellent insights.
23:03 Barbara,
23:03 over to you.
23:10 OK,
23:11 now let's turn attention to carbon offsets.
23:14 It's a very different story than carbon pricing.
23:17 So,
23:18 um,
23:18 offset
23:19 programs
23:20 are often appended to carbon pricing programs,
23:23 they allow
23:25 an emitter to pay someone else to reduce emissions instead of
23:29 them reducing their own emissions under a cap
23:32 or sometimes instead of paying a carbon tax.
23:35 And I've studied the quality of carbon offset programs for the last 20 years,
23:39 um,
23:40 looking at a,
23:40 at a range of of programs,
23:44 and in general,
23:45 carbon offset programs have worked dismally.
23:47 It's common for them to overcredit 10 times or more.
23:51 And overcrediting matters because to the extent that offsets are used,
23:56 they can undermine the effectiveness of the emissions cap
23:59 or regulatory system,
24:01 and when they're used by companies,
24:04 they can be used by companies to sell
24:06 carbon neutral products that are not carbon neutral.
24:12 Folks,
24:12 can we put up the slides?
24:25 OK,
24:26 thank you.
24:27 Uh,
24:28 so for the next
24:30 15 minutes or 17 minutes or so.
24:33 Um,
24:34 I'll,
24:35 I'm going to make the,
24:36 the three points.
24:37 Um,
24:38 one is that
24:39 most major offset programs to date have significantly overcredited.
24:44 Um,
24:45 I'll explain the common sources of overcrediting over
24:48 the project types that have generated the most credits
24:51 over 3 major
24:53 carbon offset markets.
24:55 Um,
24:55 second,
24:56 I'll describe,
24:57 um,
24:59 Basically why I'm having the same conversations today about poor quality as
25:03 I had 20 years ago when I started doing this research.
25:06 Why such persistent and
25:08 um
25:09 uh deep overcrediting
25:11 and
25:12 I'll I'll argue that poor quality is inherent
25:15 to the underlying incentive structure of carbon offsets.
25:19 And then I'll discuss a way forward,
25:20 and I'll conclude that given the 20 year history of carbon offsets,
25:23 given the underlying quality issues,
25:26 I think we,
25:27 we need to move
25:29 from
25:30 the from carbon offsets,
25:32 and I'm putting forward an idea of a
25:34 contributions approach.
25:38 So let's discuss the first
25:40 major carbon offset program,
25:42 which was established under the UN
25:44 under the Kyoto Protocol.
25:46 So under the Kyoto Protocol,
25:47 industrialized countries had caps,
25:49 developing countries didn't have caps,
25:51 and industrialized countries argued,
25:53 you know,
25:53 greenhouse gasses are well mixed in the atmosphere.
25:55 Why do they need to reduce emissions
25:58 domestically?
25:58 Shouldn't they be allowed to reduce emissions anywhere in
26:00 the world that is that where it's cheapest?
26:03 Um,
26:04 and I did field research in India on the outcomes of the program,
26:08 uh,
26:08 focusing on
26:10 grid-connected renewables and hydropower,
26:13 um,
26:14 which
26:17 I don't know if I can point
26:19 anyway,
26:19 it's the right most together that they,
26:22 they generate the most,
26:23 the most credits,
26:24 um,
26:25 and they both hydropower and renewable energy is the same methodology.
26:30 So I looked at them
26:31 together.
26:33 Um,
26:33 and methodologies are the backbone of carbon offset programs.
26:37 They define what projects are allowed to participate
26:39 and how to estimate and monitor emissions reductions under them.
26:44 And I found that
26:46 the large majority of these projects most likely
26:50 didn't reduce emissions at all.
26:51 The program mostly paid project developers to develop projects they most,
26:56 they were likely to build anyway or they had,
26:58 they were already building.
27:00 And the problem was that
27:02 the UN cast a very wide net
27:05 in what project types were allowed to participate
27:09 and required every project developer to prove that they wouldn't have gone
27:11 forward with the project were it not for the offset incentive,
27:15 the offset income.
27:16 And what I saw was that what I found in
27:19 this research was that it was very easy for project developers
27:22 to show that cost effective projects were not cost effective,
27:26 such as by
27:27 strategically choosing assumptions that go into a financial assessment,
27:31 um,
27:32 or by describing barriers to to projects.
27:36 And what happened was,
27:37 um,
27:38 high levels of overcrediting and non-additional
27:41 participation kept prices too low.
27:45 For that incentive to really affect new to incentivize new mitigation.
27:51 Um,
27:53 Adverse selection happened when and that
27:57 that that phenomenon is adverse selection right the first projects to participate
28:02 are the ones that
28:03 cost the least those are the ones that would have gone ahead anyway.
28:07 I concluded that the large majority of the projects are non-additional,
28:12 um,
28:12 not just in India,
28:13 but across,
28:14 across,
28:14 across the world,
28:16 and another article after mine Keal.
28:19 did a broader review of,
28:20 of more project types and and puts a number on that estimated that 85% of projects
28:26 most likely were non-additional or overcredited.
28:32 I then turned attention to California's offset program,
28:35 which was structured in a in a different way,
28:37 and I believe a much better way.
28:39 It was structured specifically to address the
28:41 quality issues with its predecessor program.
28:44 What California did is
28:46 narrow instead of casting a wide net and requiring every project developer to prove
28:51 the additionality of their project,
28:53 they defined a narrow set of project types.
28:56 And that were unlikely to move forward on their own,
28:59 that were likely to be affected or incentivized by the offset income.
29:04 And
29:05 um I,
29:07 I study the improved forest management,
29:10 which is the project type of 3 quarters of California
29:14 credits um on the mandate and the compliance market,
29:18 but these credits also generated over a third of all credits from projects in the US,
29:24 including the voluntary market.
29:26 Um,
29:29 And
29:31 What I and others have found is again,
29:35 A better structure,
29:36 but
29:37 widespread overcrediting
29:39 and
29:40 the way the protocol works,
29:41 the way to improve forest management protocol works is that
29:44 it allows any forest landowner anywhere in the US
29:48 to generate credits that they commit to holding
29:50 more carbon on their landscape than the baseline,
29:53 where the baseline for the most part is set at the average for that forest type.
29:57 Now there's heterogeneity on the,
29:59 on the landscape,
30:00 and what we would expect is again,
30:02 adverse selection.
30:03 Where the first forest landowners to participate are the ones that,
30:07 uh,
30:08 participate in costs the least that are already holding more carbon on their land,
30:12 um,
30:12 whether it's for climate reasons,
30:14 for climatic reasons,
30:15 ecological reasons,
30:17 or the type of timber they're producing,
30:19 um,
30:20 already are holding more carbon on the landscape than
30:22 the average so that they can generate credits,
30:24 um,
30:25 without any change,
30:26 and that's exactly what we see.
30:28 So the first two articles there,
30:30 um,
30:31 use remote sensing imagery.
30:34 To and found that
30:36 they found no uh
30:37 uh uh statistically significant difference in forest management
30:43 forest management practice
30:45 in the project areas compared to the past,
30:47 how they historically managed the lands and compared to control lands.
30:52 Now let's say um
30:54 some of these projects really would have logged aggressively
30:58 to bring their forest lands down to the average.
31:01 An earlier study that that that I did was on leakage
31:05 where I found that the protocol systematically underestimated
31:11 the impacts of,
31:14 of
31:14 when you reduce logging on participating lands,
31:17 but you don't change the demand for timber products,
31:18 of course you get some.
31:20 Uh,
31:21 uh,
31:21 uh,
31:21 uh,
31:22 displacement to other lands,
31:24 and it dramatically underestimated
31:26 the impact of leakage so much so though that it
31:30 overcredited 5 times.
31:32 It shows a very,
31:33 it uses a very low leakage rate
31:36 and it averages leakage over 100 years rather than deducting it at the same time that
31:41 uh avoided deforestation is credited.
31:45 So what we see here in some is that it's much better structured,
31:49 but we still have adverse selection and the quantification methodologies
31:53 in
31:54 in several ways are not science aligned.
31:59 I then
32:00 turned attention to the voluntary carbon market,
32:03 um,
32:03 which generates credits for voluntary use such as by companies,
32:07 universities,
32:08 other institutions to meet
32:10 targets like carbon neutrality.
32:13 And I studied again the project types of the
32:16 the project type of the most credits,
32:18 which is red
32:19 also that means avoided deforestation.
32:23 Um,
32:24 and I also did a study of cook stoves in the purple,
32:27 um,
32:28 that,
32:28 uh,
32:29 is the fastest growing offset project type.
32:32 I brought together a team of researchers and
32:34 we comprehensively looked at the major elements of
32:38 quality of avoided of the four main avoided deforestation
32:43 methodologies.
32:45 And a few things
32:47 we found
32:48 overcrediting under every rock we turned.
32:52 And
32:53 um
32:54 we were able to explore why what is what is happening?
32:57 Why is there so much overcrediting and what we found is flexibility.
33:01 That the protocols were written in a way that allowed
33:04 a wide range of projects,
33:06 a wide range of forests,
33:08 uh,
33:09 to participate across the globe,
33:11 um,
33:11 and project developers when confronted with,
33:15 uh,
33:16 flexibility in how they can set the baseline,
33:18 how they can assess leakage,
33:20 um,
33:21 especially given high levels of uncertainty in both
33:24 mean methodological choices that led to more credits rather than less,
33:27 you know,
33:28 why wouldn't they?
33:29 And the third party verifiers that are the enforcers of quality in the system,
33:33 they didn't enforce conservativeness,
33:35 they didn't even often enforce common sense.
33:39 They just,
33:40 they allowed projects to move forward if the
33:42 quantification methods were allowed by the methodologies.
33:46 And one other
33:48 factor that I want to mention
33:50 with red is that your work,
33:52 you know,
33:52 these projects are working,
33:54 um,
33:54 to avoid deforestation,
33:56 uh,
33:57 uh.
33:58 Around the globe,
33:59 um,
34:01 this project type could not be more important to be effective.
34:06 What we see is that many of these projects,
34:08 or most of these projects,
34:10 target smallholders rather than the
34:12 major industrial drivers of deforestation because
34:15 it's cheaper to do so.
34:17 And while they could generate credits against fictitious baselines,
34:21 um,
34:22 and so.
34:24 Many of most of these projects,
34:27 uh,
34:27 uh,
34:28 restricted
34:29 the restricted
34:31 forest communities from their,
34:33 their use of forests and also
34:36 Some of these projects came at a real risk of harm to forest communities.
34:41 Uh,
34:42 so the reason,
34:43 oh,
34:43 and really quickly,
34:45 so we did a comprehensive assessment of cook stoves offsets looking across all of
34:50 looking across all the major,
34:51 uh,
34:51 uh,
34:51 uh,
34:53 factors that go into quantifying emissions reductions
34:56 across,
34:56 um,
34:57 a sample of the projects on the market and found overcrediting of 10 times.
35:02 So the reasons that have highlighted over the three generations of offset
35:06 programs,
35:07 um,
35:07 are common among many project types.
35:11 So the question is,
35:14 Why such persistent overcrediting?
35:16 There,
35:16 there,
35:18 there's,
35:19 um,
35:20 clearly a structural reason why
35:23 20 years of learning by doing
35:25 we get the same,
35:26 the same outcomes,
35:27 and I believe it's these things,
35:29 these three things working together.
35:31 We have high level,
35:32 high levels of uncertainty.
35:34 Um,
35:35 we know how to measure emissions.
35:36 It's much harder to measure emissions reductions because you have
35:38 to measure them against the counterfactual scenario that never happened and
35:42 Uh,
35:42 it is unobservable,
35:45 um,
35:45 and information asymmetry,
35:46 the project developer always knows a lot more about what they would
35:49 have done without the offset income than any verifier or program administrator.
35:53 These high levels of uncertainty are being deliberated by a
35:56 set of market actors that all benefit from excess crediting.
36:00 So the whole idea of the market is
36:03 for buyers to be able to find the least cost emissions reductions.
36:07 Project developers want to get,
36:09 uh,
36:10 earn more credits for doing less adverse selection.
36:14 Third party verifiers are hired directly by the project developers,
36:17 so they have a conflict of interest to rule leniently,
36:20 um,
36:20 to be hired again,
36:22 especially in the context of high levels of subject uncertainty and subjectivity.
36:28 Um,
36:28 and the,
36:28 the registries themselves,
36:31 uh,
36:31 the,
36:31 the program creators
36:33 on the voluntary market,
36:35 they're vying for market share,
36:37 and in compliance markets,
36:39 there's
36:40 political pressure to keep offset prices low.
36:43 So what you get is a race to the bottom that if one methodology
36:48 were to
36:49 be tightened up and science aligned and not overcredited,
36:53 the market flows to
36:54 the other methodologies.
36:58 So what is the way forward,
37:00 and
37:01 I think
37:04 I'll argue 3 things.
37:06 One is that efforts to create quality offset programs are unlikely to succeed.
37:13 Um,
37:18 Because of,
37:18 because of this,
37:19 the history and the structural reasons.
37:22 We need to shift from offsetting to contributions claims.
37:26 And
37:27 what I'm most excited about.
37:29 Going forward is a shift from offset markets to direct contributions,
37:34 and let me discuss each of those.
37:36 So,
37:38 one is
37:39 um
37:41 Even though I think it is
37:43 unlikely that we're going to
37:45 be able to achieve an offset market,
37:48 um,
37:48 that is quality and not significantly overcredited,
37:52 it's still worthwhile to
37:54 uh have have uh quality methodologies that
37:58 can be used for contributions approaches,
37:59 they can be used for offset
38:01 programs,
38:02 you know,
38:02 a narrow set of offset project types that
38:04 we're offsetting really work with really works for.
38:09 So how do you do that?
38:10 One is most important,
38:13 I believe,
38:13 is to remove conflicts of interest.
38:16 So that means methodology should be designed and evaluated against clear
38:20 criteria by independent experts with
38:22 interdisciplinary scientific and practical expertise.
38:26 Verifier should be hired by independent bodies
38:29 rather than by the project developers themselves,
38:32 and credit calculations
38:34 should be released publicly so that independent parties like us
38:38 can evaluate quality.
38:41 And then
38:42 by
38:43 criteria,
38:44 I put forward
38:46 doing a comprehensive over undercreting analysis
38:50 where you compare methodologies and how
38:52 they're implemented in practice by projects
38:55 against the scientific literature and best practice in a quantitative analysis.
38:59 A benefit is that it acknowledges that
39:02 some projects are going to over credit.
39:03 There's going to be some non-additional crediting.
39:06 But you can structure your program so that
39:08 there's enough conservativeness and undercrediting so that
39:12 programmatically
39:13 it's a quality program you're not overcrediting.
39:16 You want to assess uh quality elements,
39:20 um.
39:23 Um
39:25 I'm going to
39:28 Um,
39:29 OK,
39:29 uh,
39:30 assess,
39:31 assess quality elements,
39:33 taking into account,
39:34 um,
39:35 uh,
39:35 the lean towards overcrediting all the things that
39:37 we've been talking to and treating uncertainty conservatively.
39:43 I,
39:44 um,
39:45 I think.
39:47 It's really important to shift from offsetting to contributions claims
39:52 where offsetting claims are,
39:55 you treat your reducing your own emissions
39:57 as equivalent to paying someone else to reduce
40:00 their emissions,
40:00 and you can call it a net number.
40:02 The problem there is,
40:03 uh,
40:04 it creates a disincentive to reduce emissions,
40:07 a company that dramatically reduces their emissions and
40:10 buys offsets for just the small remainder,
40:13 and another company that
40:15 Um,
40:15 and it's like crazy and just buys,
40:17 buys cheap carbon credits.
40:18 They look the same.
40:19 They can both claim the same
40:21 carbon neutral or net zero claim.
40:25 And if you switch to a contributions claim where you don't let those two numbers be
40:31 netted
40:31 and a company
40:33 um can discuss how much it's reduced its own emissions,
40:36 it can discuss its contributions,
40:38 it's a more complex
40:39 claim,
40:39 but it's more honest
40:41 and it refocuses attention on direct
40:44 emissions reductions and it creates flexibility
40:46 to support a wider range of activities based on a wider set of goals.
40:50 And my final,
40:52 uh,
40:52 substantive slide.
40:54 That opens the creates an opportunity to
40:59 shifting from offset markets
41:01 to direct contributions
41:03 and an offset market,
41:04 writes a set of rules and let and lets the market go and find the cheapest reductions,
41:09 direct contributions,
41:11 um,
41:12 uh.
41:14 Moves us out of that
41:16 marketplace
41:18 and buying a commodity
41:19 into a space of
41:21 uh what a company would do if they're uh
41:24 uh contracting with a supplier or giving a donation,
41:28 you would,
41:28 you would vet organizations,
41:30 you would vet programs,
41:31 you would build a relationship with them.
41:33 Um,
41:34 so,
41:35 uh,
41:36 contributions approach would mean giving directly to NGOs,
41:40 giving directly to government programs,
41:42 giving directly even to companies such as those distributing,
41:45 uh,
41:46 very fuel efficient cook stoves.
41:49 Um,
41:50 characteristics of the direct contributions approach are
41:53 you directly contribute to those entities.
41:56 So money is going directly to those entities,
41:59 not to brokers and consultants,
42:00 etc.
42:01 You provide you can provide funds upfront when they're most needed.
42:05 Um,
42:06 you can denominate primarily in money rather than in tons.
42:09 You can still quantify
42:11 the greenhouse gas benefits,
42:13 but you denominate the,
42:14 the,
42:14 the contribution in money.
42:18 And that
42:19 it invites taking many more factors into account,
42:22 not just cheap carbon.
42:24 Um,
42:24 and it also allows for supporting a
42:26 wider range of activities to drive decarbonization,
42:29 including some that are hard to quantify the greenhouse gas benefits,
42:34 for example,
42:34 like in the agricultural
42:36 sector,
42:37 supporting a range of activities to
42:39 bring farmers into different practices which can be demonstration projects,
42:44 technical assistance,
42:45 incentive programs,
42:47 outreach activities,
42:49 and be nimble and adapt over time.
42:52 Um,
42:56 And lastly,
42:56 I think we don't have time to waste on programs that have already
43:03 disproven themselves
43:04 and I'm very excited about
43:07 shifting the framework
43:10 from offsets to to direct contributions.
43:13 I think it can have much better impacts.
43:20 Thank you very much,
43:21 Barbara.
43:22 That was very insightful and bit depressing,
43:24 right?
43:25 Uh,
43:25 so,
43:26 let me turn now to Kaushik for your,
43:29 uh,
43:29 presentation on India's pollution program in Gujarat.
43:36 Um,
43:37 thanks,
43:37 Ami.
43:38 Let me just grab the water.
43:45 As my kind of slides come up,
43:47 I think
43:48 being the last speaker of the day,
43:51 uh,
43:51 it just falls to me to
43:53 put up whatever little defense I can for
43:56 economic instruments to deal with environmental problems.
44:00 Um,
44:01 This
44:02 is a piece of work that has been ongoing in a city in India
44:06 called Surat for the last 15 years.
44:10 It's an experiment to see whether we can use market-based instruments to deal with.
44:15 Environmental issues and it's an experiment that we've constantly kind of evolved
44:20 and evaluated
44:21 and gotten to a point where we think that this is a viable
44:26 tool that can be used to deal with at least a certain kind of environmental problems
44:31 and we're kind of trying to deploy it much more extensively in India and elsewhere.
44:35 So what this presentation does is of course kind of talk
44:38 about Michael's paper which came out in the Quarterly Journal of Economics
44:42 a couple of months back,
44:44 but also talk about what that paper has meant in terms of our activities
44:49 and
44:49 actually using
44:52 a textbook tool to act to create a
44:56 create an economic service that deals with environmental issues.
45:00 So what's the
45:01 problem that we're dealing with?
45:04 Essentially
45:05 air quality
45:06 and pollution,
45:07 and let me kind of just show you exactly what that means.
45:10 Shamik,
45:11 you kind of talked about
45:12 what air quality means in terms of lives lost.
45:16 On an average,
45:17 air quality causes
45:19 more damage than
45:22 Tobacco,
45:22 alcohol,
45:23 terrorism,
45:24 HIV,
45:25 malaria,
45:26 and this impact is very significant.
45:28 2 years or over 2 years of everyone's life globally.
45:32 I mean when you're living in a city in Delhi
45:35 like I do,
45:36 it's almost 8 years of your life,
45:37 and that's,
45:38 I mean,
45:39 I'd argue,
45:39 a fairly chunky piece of your existence.
45:42 So you really kind of
45:45 Dealing with this challenge on a real-time basis,
45:48 we're also dealing with this challenge on
45:49 a real-time basis where this trade-off between
45:52 the aspirations of a population of nearly 1.5 billion
45:57 people wanting to achieve a certain level of prosperity
46:01 and having to
46:03 deal with air quality and emissions that come from using fossil
46:06 fuels as extensively as is happening in a country like India,
46:10 you kind of have to start to think about this
46:12 as not necessarily.
46:14 Issues that are in tension with each other,
46:16 but how do you kind of resolve this tension
46:18 and that's really where we are trying
46:20 to use market market-based instruments to kind of
46:22 solve,
46:23 uh,
46:23 for that problem
46:25 because
46:26 historically.
46:27 Everywhere in the world,
46:28 what we've tried to do to deal with air quality and pollution
46:32 is essentially use
46:33 a plethora of regulatory instruments,
46:35 mostly command and control,
46:37 and these have been
46:39 so extensively deployed
46:42 since the,
46:43 since the early 60s in the developing,
46:46 in the developed world and then subsequently in the developing world.
46:49 In the 90s and thereafter,
46:51 that
46:52 the number of regulatory instruments that even exist
46:54 in a country like India is really,
46:56 really incredible to just deal with air quality and pollution,
46:59 but the impact,
47:00 as you saw in the previous slide,
47:02 hasn't been as dramatic as you would like that to be.
47:05 So there is something missing in this equation
47:08 that you kind of need to fix.
47:10 And if you kind of think this through,
47:11 why is this a problem?
47:13 Because how do you deal with
47:15 Air quality and emissions from industrial units
47:18 in
47:19 most parts of the world.
47:20 This is a really,
47:22 really labor intensive regulatory capacity intensive
47:26 process that cannot be deployed at an extensive scale anywhere,
47:30 even in,
47:31 even in a
47:32 very well.
47:33 Equipped regulatory capacity that you might have in the United States or in Europe.
47:37 It involves essentially
47:39 a person climbing up a stack,
47:41 an emissions stack,
47:42 a chimney stack in an industrial unit,
47:44 collecting a sample of emissions for a certain period of time,
47:48 taking that sample back to a laboratory
47:50 and testing whether that actually meets the environmental
47:54 standards or the concentration emissions standards
47:56 for that particular plant or not.
47:59 This is something that you clearly can't be doing on a daily or a constant basis.
48:02 This probably happens once or
48:04 twice in a year
48:06 for most locations in the US,
48:08 in countries like India,
48:09 perhaps even less
48:11 frequently.
48:12 And even if you were to be able to do that,
48:13 this does not really solve the problem
48:15 of air quality and emissions from industrial units
48:18 on a continuous basis.
48:20 So what we've tried to do in India
48:24 in Surat is to try and see whether the use of a market-based instruments.
48:30 Added to emissions monitoring program that kind of uses
48:34 the state of the art emissions monitoring and control
48:37 equipment,
48:38 can that be a way to kind of solve for emissions and air quality?
48:42 And
48:43 this is the experiment that we kind of carried out in Surat
48:46 that took over 10 years to kind of set up and develop.
48:49 This involved
48:50 right from the initial stages of working with the Ministry
48:53 of Environment at the federal level in India to.
48:55 Identify the role that
48:58 cap and trade schemes,
48:59 emission trading schemes could actually play
49:00 in dealing with industrial air pollution,
49:04 working with the pollution control boards,
49:06 the pollution regulators in India to develop standards and
49:11 regulations of what kind of equipment can be used
49:14 to measure emissions and how that emission measurement can be.
49:19 Put together in a manner that's kind of transparent,
49:22 above board,
49:23 without discretion,
49:24 and cannot be tampered with,
49:26 providing data on a 24/7 basis
49:29 to a central service sitting with a pollution regulator.
49:32 Identifying folks who will actually go and do the work
49:36 of installing these emissions control devices,
49:38 calibrating them,
49:39 making sure that they run
49:41 exactly as they're designed to run and
49:45 Set up
49:46 trading mechanisms,
49:47 a trading platform,
49:49 bring industry partners on board,
49:51 show them
49:52 how trading platforms actually work,
49:54 how they can actually measure their emissions,
49:55 how they can actually trade their
49:57 emissions,
49:58 and then.
50:00 Having launched this program in 2019,
50:02 go through a fairly extensive process of
50:05 randomized control
50:07 evaluations to see whether the emissions trading scheme
50:11 is actually having an impact or not,
50:13 and coming to a point where
50:15 the success of the program
50:17 in this one location in Gujarat in India
50:20 has kind of led to a
50:22 proliferation of using this tool within the
50:24 state across pollutants and across locations,
50:27 but also in other parts of the country as well.
50:31 And this
50:33 truly involved a lot of sweat and blood and a lot of kind of grimy effort.
50:38 We're
50:39 going through the process of installing these emissions control devices
50:44 across 300 odd industrial units in the city of Surat,
50:47 making sure that these
50:49 are providing data on a continuous regular basis,
50:53 that data is being
50:54 evaluated,
50:55 tested,
50:55 and made sure that it's not spurious.
51:01 Working with the regulator.
51:03 Sitting in their offices designing and implementing the
51:07 program in partnership with these officers and their
51:10 inspectors
51:12 because the idea here is to translate,
51:15 essentially a textbook tool
51:17 into the regulatory and the legislative framework that exists for
51:21 emissions management or pollution management in a state in India.
51:25 So you have to kind of work through
51:27 the entire rulebook of how emissions
51:30 are controlled and regulated at the 115 odd regulatory
51:35 frameworks that I kind of highlighted earlier
51:38 that kind of exist to deal with air quality in India.
51:43 Working with
51:44 the regulator as well as industry partners to make sure that
51:48 we are building their capacity,
51:49 they know exactly what the scheme means,
51:51 how that scheme is supposed to run,
51:53 and make sure that
51:54 they are well equipped to be able to use this tool
51:57 on a firm basis or on a regulator basis
52:00 to be able to
52:01 run the scheme itself.
52:05 To the point of
52:07 taking them through a series of mock simulations of
52:10 what an emissions trading scheme would look like.
52:12 This is the trading platform
52:14 that the firms use
52:15 to carry out trading for,
52:17 uh,
52:19 particulate matter for these 300 odd firms
52:22 in Surat,
52:25 and
52:25 just to kind of
52:27 show.
52:28 This entire process has been
52:31 evaluated through a fairly rigorous and detailed exercise
52:36 where we
52:38 took these 300 odd firms in Surat,
52:41 divided them into two groups the treatment group,
52:45 which
52:47 were,
52:48 which were kind of set up in the emissions trading scheme,
52:50 and a control group which continued to operate as
52:54 though it was in the traditional command and control.
52:57 A regime
52:58 and evaluating the differences
53:00 of what that meant
53:01 and
53:02 ladies and gentlemen,
53:03 I mean the results are truly quite dramatic.
53:07 The first,
53:08 and this is the reason why we were able to bring the regulator on board.
53:11 This is the reason why
53:13 the government kind of came on board to try out this experiment.
53:16 Essentially the problem was noncompliance.
53:19 Essentially the problem was that industries were not meeting their emissions
53:25 emissions standards.
53:26 And that's something that we kind of were able to establish very,
53:29 very quickly that the moment you put in
53:31 place the scheme and you allow the flexibility,
53:33 something that
53:35 Barbara Karo pointed out could be
53:36 a difficult thing to manage,
53:38 but the moment you can provide this flexibility to firms
53:41 to be able to meet their emission targets by buying permits
53:44 and making sure that the firms
53:46 who were meeting their targets but could do even better than that.
53:51 You increase the level of compliance in the market to nearly 100%.
53:55 This
53:56 1% or less than 1% compliance,
54:00 fun story,
54:01 this was in the first compliance period that we had,
54:03 and essentially two of the most politically well connected firms
54:09 in this in this textile cluster said that.
54:13 Sumi,
54:14 what will you do?
54:15 And that's kind of
54:16 interesting when
54:17 the chairman of the pollution control board
54:20 called up Michael
54:21 and said that,
54:23 so what do you want me to do in this case?
54:24 And essentially the response was that this is your
54:28 opportunity to draw a line in the sand.
54:31 If you establish
54:33 your authority and your ability to manage and run this market.
54:38 That's what will kind of give you the regulatory
54:41 credibility that you need to be able to run the market
54:43 in a manner that you do not have leakages or noncompliance.
54:48 And subsequently
54:50 you'd get a
54:51 hasn't been a single
54:53 compliance period where we've had firms not comply with their emission targets,
54:58 and that's really the reason why
55:00 the Gujarat Pollution Control Board
55:02 has kind of continued to use this tool and now
55:04 is trying to deploy it across pollutants and across different
55:08 industrial clusters to deal with
55:10 a variety of environmental issues.
55:14 But the reason I think
55:16 for me and for us
55:17 the scheme was an extremely important success is that
55:21 firms that were there
55:23 in the command and control
55:25 had their emissions
55:27 on an average about 20 to 30% higher depending on
55:30 which compliance period.
55:33 So the fact that there was an emissions trading scheme that allowed firms
55:37 to reduce their emissions much more
55:39 than the standards required them to do
55:41 and be able to monetize that improved environmental behavior
55:45 led to
55:46 their emissions,
55:47 the market
55:49 cohort emissions,
55:50 being about 20 to 30% lower,
55:52 and that,
55:53 I think,
55:53 is a very,
55:54 very powerful tool,
55:55 a powerful outcome.
55:57 Thanks,
55:58 Shamik.
55:58 I'll
55:59 wind up quickly,
56:01 but
56:01 this is the piece that I think makes for the success of the program.
56:07 When the firms in the command and control regime saw that the compliance cost
56:12 of the firms in the market
56:14 was lower by about 11%,
56:17 there was a clamor amongst all the firms that
56:19 were not in the market to join the market.
56:23 And
56:24 if you kind of think about it,
56:25 this is obvious.
56:25 This is Economics 101.
56:26 What does a market do?
56:27 A market achieves.
56:29 A certain outcome at the least cost,
56:32 and this is that cost
56:33 reduction that the market was able to achieve.
56:36 And that's kind of what's led to
56:38 the third part of my presentation,
56:40 the scale up activity that has happened,
56:42 but just to kind of close this out,
56:44 uh,
56:45 the cost-benefit ratio here that we've estimated is about
56:50 215 to 1.
56:51 This is an incredible number.
56:54 This is an incredible number of a population of a
56:56 city of a population of about 20 million people.
56:59 For just under 20 million people,
57:00 the asset drain program in comparison
57:03 in the US had a cost-benefit ratio of about 50 to 1.
57:08 So
57:08 the
57:10 impact that
57:11 the use of this economic instrument
57:13 has had
57:14 in terms of improving
57:16 the cost,
57:18 improving the,
57:19 the,
57:20 the,
57:20 the benefit of the society
57:22 is really,
57:22 really impactful.
57:23 But let me kind of take the last few
57:26 minutes of my presentation to show what this has actually meant.
57:30 Having seen this
57:32 happen in Surat in Gujarat.
57:36 The Gujarat Pollution Control Board
57:38 essentially wanted to kind of
57:40 use this as a tool and wants to use this as a tool
57:43 for
57:44 almost everything that they want to do.
57:47 Now,
57:47 clearly you can't use an emissions trading
57:50 scheme for every sort of environmental problem.
57:52 I mean,
57:52 you clearly won't be able to use this
57:54 for,
57:55 for instance,
57:55 dealing with transport sector emissions.
57:58 You need large point-based
58:00 emitters to be able and with enough heterogeneity
58:03 for an emissions trading scheme to work.
58:05 But having kind of
58:07 done this exercise once in Surat,
58:10 we have kind of gone through the process of scoping which
58:13 of these environmental challenges in Gujarat can be
58:16 solved using
58:17 a
58:17 market-based instrument like this,
58:19 and the scheme is now expanded to include the textile cluster in a big city in
58:24 Gujarat called Ahmedabad.
58:25 And we are now
58:26 in the process of designing an affluence-based,
58:30 uh,
58:31 affluence-based emissions trading scheme for two
58:34 industrial clusters in Gujarat for the,
58:37 for the Gujarat Pollution Control Board.
58:40 A neighboring state,
58:41 Maharashtra,
58:42 one of the largest industrial powerhouses
58:45 in India,
58:47 is now
58:48 on its way to develop a SO2 uh market.
58:51 So this is going to be a statewide SO2 market.
58:54 It would cover about 300 industrial units,
58:56 and this would be truly,
58:59 truly extensive because this will include electricity.
59:01 This will include petchem.
59:02 This will
59:03 include fertilizer.
59:05 This will include pharma.
59:06 This will include refining.
59:08 This would include cement and steel.
59:11 So this is going to be a really,
59:13 really remarkable.
59:14 Experiment this would,
59:16 uh,
59:16 this is kind of a population of 140 odd million people
59:20 so you can imagine
59:21 that the Surat cost-benefit ratio was 215.
59:24 This could easily,
59:25 I can imagine be a four digit number
59:28 and similarly we've kind of started
59:31 the initial steps of scoping out a similar market for,
59:34 uh,
59:35 uh,
59:35 another neighboring state to Gujarat,
59:36 Rajasthan.
59:39 And now
59:41 it's almost like the floodgates have opened.
59:43 We are having conversations with a number of states in
59:46 India and a number of other geographies around the world
59:49 to see whether this particular tool is viable and a solution and can actually
59:56 solve for environmental challenges of a particular kind
1:00:00 across these different geographies.
1:00:03 And
1:00:04 that's it.
1:00:06 This is what I'm offering.
1:00:08 So this is kind of bringing
1:00:09 this
1:00:10 incredible piece of research,
1:00:12 this extremely
1:00:14 intense period of design and implementation
1:00:18 to getting to a point
1:00:19 where
1:00:20 My,
1:00:22 my ultimate objective is that this is a
1:00:25 plug and play solution.
1:00:27 So Surat took 10 years to do.
1:00:30 I'm aiming that our market in Maharashtra is up
1:00:33 and running in a period of about 18 months.
1:00:35 In an ideal world,
1:00:37 this would be a plug and play solution where I can kind of
1:00:40 offer this as a service.
1:00:43 As a,
1:00:44 as an economic service
1:00:46 to any regulator,
1:00:47 any pollution,
1:00:48 uh,
1:00:49 regulator around the world
1:00:50 where we kind of go in,
1:00:51 sit with them,
1:00:52 design the solution,
1:00:54 and
1:00:54 offer them the,
1:00:56 uh,
1:00:56 give them the market
1:00:57 to run
1:00:58 on a
1:00:59 on
1:01:00 on a period
1:01:01 until kind of this environmental challenge is actually dealt with.
1:01:04 So
1:01:05 just to kind of highlight the fact
1:01:07 this is started with this incredible piece of research
1:01:12 that
1:01:14 the course theorem is
1:01:15 to this incredible piece of research that
1:01:17 Michael and colleagues published earlier this year
1:01:19 to now a solution that we are actually designing and implementing
1:01:24 on the ground.
1:01:25 Thank you.
1:01:29 Kaushik,
1:01:30 thanks so much.
1:01:30 That was
1:01:31 really inspiring.
1:01:33 And uh I hope you tell us later about how you're going to plan to scale up the work.
1:01:37 But first,
1:01:38 let me turn to Carolyn.
1:01:39 Carolyn,
1:01:40 you've heard the three presenters,
1:01:42 and you've heard about both pollution and emissions
1:01:45 using market instruments and and regulatory instruments.
1:01:48 So give us a little bit of your reflections
1:01:50 and your takeaways from this.
1:01:52 Yeah,
1:01:52 thank you and thanks to all of you.
1:01:53 Um,
1:01:54 I thought this was a really
1:01:55 fascinating,
1:01:56 um,
1:01:57 session,
1:01:58 um.
1:01:58 And so,
1:02:00 uh,
1:02:00 you know,
1:02:01 maybe taking it back to the theme here,
1:02:04 um,
1:02:04 there is this,
1:02:05 you know,
1:02:07 strong popular populist opinion that,
1:02:10 um,
1:02:11 You know,
1:02:11 a mistrust of
1:02:13 emissions pricing as a means of actually reducing emissions.
1:02:19 There isn't a lot of faith in that.
1:02:20 There are a lot of,
1:02:22 you know,
1:02:23 people
1:02:24 view
1:02:25 carbon pricing as
1:02:27 a tax and redistribution scheme.
1:02:30 And not
1:02:33 and not as,
1:02:34 as a driver
1:02:35 of,
1:02:36 of decarbonization.
1:02:37 In fact,
1:02:37 in Canada,
1:02:38 we saw some backsliding.
1:02:40 So Mark Carney prior to the
1:02:43 um
1:02:44 to the election,
1:02:46 uh,
1:02:47 just canceled the carbon tax on on households as just too politically toxic.
1:02:54 Um,
1:02:54 so it was nice to see from Jan we
1:02:56 have really solid evidence that pricing mechanisms do work,
1:03:01 um,
1:03:02 and,
1:03:02 and in the,
1:03:04 um,
1:03:04 the goal of reducing emissions.
1:03:06 So,
1:03:07 so then we kind of get to the question of,
1:03:09 of where and how,
1:03:11 um,
1:03:11 and how to make these,
1:03:13 these feasible.
1:03:14 So I thought it was really,
1:03:15 um,
1:03:16 interesting and so one of your,
1:03:17 um,
1:03:18 one of your insights is that,
1:03:19 um.
1:03:20 Yeah,
1:03:20 you,
1:03:21 you found that the emissions reductions
1:03:23 were larger in industry
1:03:25 than in other sectors like households
1:03:28 and,
1:03:29 um,
1:03:29 and I,
1:03:30 I think we,
1:03:31 we do see that,
1:03:32 um,
1:03:32 so emerging.
1:03:33 So the latest state trends of carbon pricing by my colleagues here at the bank,
1:03:37 um,
1:03:38 show that,
1:03:39 um,
1:03:40 today.
1:03:41 Um,
1:03:42 a little over half of global emissions in the power sector
1:03:46 and approaching 50% of emissions in the industrial
1:03:49 sector are covered by carbon pricing instruments now,
1:03:52 primarily emissions trading systems,
1:03:55 so that may be sort of following this,
1:04:00 uh,
1:04:01 this insight that there are more effective
1:04:06 drivers but also potentially more politically feasible
1:04:09 drivers.
1:04:10 In these sectors,
1:04:11 um,
1:04:11 but I,
1:04:12 I,
1:04:12 and also reflect,
1:04:13 you know,
1:04:13 from some of your numbers there,
1:04:15 I think that the design of the system also,
1:04:18 also matters.
1:04:19 So we saw like really big reductions from Reggie with pretty small
1:04:25 carbon prices,
1:04:26 um,
1:04:27 you know,
1:04:28 some of that may be like some of the states actually use the revenues to deepen
1:04:33 reductions by funding energy efficiency programs and demand reduction.
1:04:39 Um,
1:04:40 and,
1:04:40 and so they found that they actually
1:04:42 reduced electricity costs in some of these states
1:04:45 and deepened emissions.
1:04:47 And then when you had the sort of less
1:04:51 effective example of South Africa,
1:04:54 which actually has a higher carbon price than,
1:04:57 you know,
1:04:58 ostensibly than Reggie.
1:05:01 But you know,
1:05:01 part of the issue there is that
1:05:05 up to 90% of emissions from any given facility
1:05:10 are exempt,
1:05:11 so you're effectively rebating the tax revenues to
1:05:15 to the firms in proportion to their emissions.
1:05:18 So that really undermines
1:05:20 the effective carbon price being.
1:05:24 Uh,
1:05:25 carbon price signal.
1:05:26 But of course,
1:05:27 you know,
1:05:27 South Africa is a very different context than,
1:05:30 uh,
1:05:31 Northeastern US states and so they're also institutional issues,
1:05:35 um,
1:05:35 that we need to be cognizant of and thinking about
1:05:38 what other,
1:05:40 uh,
1:05:40 you know,
1:05:40 for emissions markets to work,
1:05:43 to what extent do we also need,
1:05:45 you know,
1:05:45 power markets,
1:05:46 uh,
1:05:47 to work,
1:05:47 to be liberalized and where,
1:05:49 um,
1:05:50 uh,
1:05:51 and,
1:05:51 and think about other market failures,
1:05:53 um.
1:05:54 So I thought that was,
1:05:56 that was very interesting
1:05:57 and I know,
1:05:58 I thought that,
1:05:59 um,
1:06:00 I think we can also talk some more about policy mixes.
1:06:04 I thought those insights were,
1:06:06 um,
1:06:07 were really compelling because,
1:06:09 uh,
1:06:10 you know,
1:06:10 showing that
1:06:11 in,
1:06:11 in a lot of situations,
1:06:13 um,
1:06:14 you get bigger emissions reductions.
1:06:16 With the policy mix,
1:06:17 partly this could be because,
1:06:20 uh,
1:06:20 you know,
1:06:21 it's hard to implement a stringent enough carbon
1:06:24 price to really send a strong signal,
1:06:26 but,
1:06:26 you know,
1:06:26 a lot of other policies,
1:06:28 infrastructure investments can enable,
1:06:30 give people
1:06:31 the options to respond to the carbon price,
1:06:36 more effectively.
1:06:37 So,
1:06:38 uh,
1:06:39 and,
1:06:39 and also on the flip side,
1:06:42 um,
1:06:42 having some carbon pricing.
1:06:44 Uh,
1:06:45 makes your other complementary policies more effective too.
1:06:48 So,
1:06:48 uh,
1:06:49 you have,
1:06:50 you know,
1:06:50 for the same renewable subsidy,
1:06:51 if you have a little carbon price there that also
1:06:55 increases the return to investments in renewable energy and so amplifies,
1:06:59 um,
1:07:00 that together.
1:07:01 Um.
1:07:03 What,
1:07:04 um,
1:07:04 so,
1:07:05 so,
1:07:05 OK,
1:07:06 so we have,
1:07:06 uh,
1:07:07 evidence that,
1:07:08 uh,
1:07:08 carbon pricing actually works,
1:07:10 um,
1:07:11 but popular opinion tends to,
1:07:13 uh,
1:07:15 show greater support for,
1:07:17 you know,
1:07:18 conventional regulation.
1:07:19 There's,
1:07:20 there's
1:07:20 survey evidence across a lot of countries that,
1:07:23 uh,
1:07:24 you know,
1:07:24 uh,
1:07:25 there's more popular support for standards,
1:07:28 uh,
1:07:29 upcoming WGR topic,
1:07:31 um.
1:07:32 Uh,
1:07:33 than,
1:07:34 than taxes,
1:07:35 for sure,
1:07:36 um,
1:07:37 and,
1:07:37 and,
1:07:37 and so we do see,
1:07:38 so in the case of India,
1:07:40 we see that there actually is quite a bit of demand
1:07:42 for regulation because the burden of air pollution is so extraordinary.
1:07:48 So there is,
1:07:49 um,
1:07:49 so there is demand for that and,
1:07:51 and,
1:07:51 and then you've ended up with an enormous number
1:07:54 of regulations,
1:07:56 our command and control regulations there.
1:07:58 And so I think this is incredibly important and showing that,
1:08:03 um.
1:08:04 Uh,
1:08:04 that market-based,
1:08:06 uh,
1:08:07 approaches are much more cost effective.
1:08:09 So,
1:08:10 so,
1:08:11 and this might be a way of like coming,
1:08:13 coming full circle and then convincing people and
1:08:16 you also mentioned in the green room that,
1:08:19 um,
1:08:21 uh,
1:08:21 you know,
1:08:21 so switching to a market-based approach is actually increased enthusiasm
1:08:26 of the firms
1:08:27 for being regulated because they felt like they were benefiting.
1:08:31 Um,
1:08:32 uh,
1:08:32 from,
1:08:33 uh,
1:08:33 from this program.
1:08:35 So,
1:08:35 uh,
1:08:35 I guess a couple questions,
1:08:37 um,
1:08:38 uh,
1:08:39 questions there.
1:08:40 I'm wondering,
1:08:41 so how,
1:08:41 how important,
1:08:42 so if my,
1:08:43 um,
1:08:43 understanding the the scheme.
1:08:45 Um,
1:08:46 the,
1:08:47 uh,
1:08:48 you know,
1:08:48 this was not
1:08:50 a redistributional scheme so much because the effectively the allowances were
1:08:56 all freely allocated
1:08:57 to the firm.
1:08:58 So like how important
1:09:00 is that aspect,
1:09:02 at least certainly in getting,
1:09:04 getting something going,
1:09:06 um,
1:09:06 uh,
1:09:06 other,
1:09:07 other folks.
1:09:08 Countries may be looking towards emissions pricing
1:09:11 mechanisms also as a source of revenue
1:09:13 for other activities that that might,
1:09:16 you know,
1:09:17 deepen energy access or
1:09:20 or you know,
1:09:20 low carbon investments
1:09:23 so,
1:09:23 so there are tradeoffs there and how you use the and allocate the revenue.
1:09:27 So I'd be curious to hear about that.
1:09:31 And also,
1:09:32 um,
1:09:33 you know,
1:09:33 often one of the motivations for carbon pricing
1:09:36 is the co-benefits,
1:09:37 the air pollution co-benefits.
1:09:39 And so I'm wondering here,
1:09:41 have you looked at,
1:09:41 thought about the
1:09:43 climate co-benefits
1:09:44 of the air pollution regulation,
1:09:46 because if it's,
1:09:46 if it's more salient
1:09:48 to,
1:09:49 to approach that regulation,
1:09:53 that can that framing help,
1:09:55 but also help
1:09:57 deepen
1:09:59 climate ambition.
1:10:00 Um,
1:10:01 because it goes hand in hand with uh these approaches.
1:10:04 Um,
1:10:05 and then,
1:10:06 uh,
1:10:06 finally,
1:10:06 Barbara,
1:10:07 um,
1:10:09 so,
1:10:09 so thinking about
1:10:11 carbon offsets and,
1:10:12 and we do see in several,
1:10:14 uh,
1:10:14 emerging economies,
1:10:16 uh,
1:10:17 interested in emissions trading systems,
1:10:20 a lot of that is also as a way to finance domestic,
1:10:24 um,
1:10:25 uh,
1:10:26 car,
1:10:26 you know,
1:10:27 carbon reduction offset offsetting activities,
1:10:30 um.
1:10:31 Um,
1:10:31 but more broadly,
1:10:33 you know,
1:10:33 I,
1:10:33 and I see within the institution there,
1:10:35 there are
1:10:36 big hopes for carbon crediting
1:10:39 as a means to generate,
1:10:41 uh,
1:10:42 climate finance.
1:10:43 Um,
1:10:44 and,
1:10:45 and so,
1:10:46 um,
1:10:47 you know,
1:10:47 so what do we do as we switch?
1:10:50 I mean,
1:10:51 we,
1:10:51 we see that
1:10:52 the,
1:10:53 you know,
1:10:53 the evidence about the massive overcrediting has,
1:10:56 has really
1:10:57 limited demand
1:10:58 for,
1:10:59 for credits,
1:11:00 um,
1:11:01 especially in compliance systems.
1:11:03 So like the EU does not allow crediting against ETS compliance,
1:11:10 um.
1:11:11 Uh,
1:11:12 but there's also,
1:11:13 you know,
1:11:13 uh,
1:11:13 voluntary,
1:11:14 voluntary markets.
1:11:16 And so thinking about,
1:11:17 so where,
1:11:18 where does demand for credits come from because these offset credit,
1:11:21 there are a lot of different kinds of offsets,
1:11:24 um,
1:11:24 so there's forests,
1:11:25 there's cook stoves,
1:11:26 renewable energy,
1:11:27 there's,
1:11:27 uh,
1:11:28 different things with very and actually removals like,
1:11:32 um,
1:11:32 direct air capture or something,
1:11:34 um,
1:11:35 and,
1:11:35 uh,
1:11:36 and then they also come with very different characteristics,
1:11:39 so.
1:11:40 Um,
1:11:41 in terms of the local community benefits,
1:11:44 um,
1:11:45 um,
1:11:46 and so as we,
1:11:48 that,
1:11:48 that are hard to quantify,
1:11:50 especially when
1:11:51 you're denominating everything in CO2.
1:11:54 And so I'm wondering as we move,
1:11:58 if we can move to more of a contributions approach as you suggest,
1:12:03 how do we
1:12:04 valorize sort of like in a holistic way,
1:12:08 all the,
1:12:09 the benefits of these different activities.
1:12:13 to um enhance demand
1:12:16 and and what do we need to do to understand like where that demand is coming from,
1:12:20 especially,
1:12:21 you know,
1:12:21 from the corporate sector and and and voluntary approaches.
1:12:25 So um
1:12:26 thank you very much.
1:12:27 Those are my uh starting for uh some discussion.
1:12:33 Thank you very much,
1:12:34 Carolyn.
1:12:34 Those were
1:12:36 really insightful comments.
1:12:38 So,
1:12:38 what we will do,
1:12:39 we have less than 20 minutes.
1:12:41 We're gonna turn to each one of you to reflect on Carolynn's comments,
1:12:45 but I may prompt you with a question as well.
1:12:47 Then we'll turn
1:12:48 to our friends here who have been patiently waiting and hopefully,
1:12:52 we'll let you all go by 6 o'clock,
1:12:54 right?
1:12:54 So,
1:12:55 uh,
1:12:55 so,
1:12:56 Yan,
1:12:56 uh,
1:12:57 Carolyn had a lot of
1:12:58 Um,
1:12:59 you know,
1:13:00 good points on your,
1:13:01 on your discussion,
1:13:02 but one of the things that struck me
1:13:05 was the role of policy complementarities on this policy mix,
1:13:09 and that carbon pricing
1:13:11 is amplified with other market-based policies,
1:13:15 particularly
1:13:16 structural economic policies are in play.
1:13:19 So tell us a little bit about this policy mix of carbon pricing.
1:13:24 And other structural market policies in,
1:13:27 in thinking about emissions reduction.
1:13:32 Yeah,
1:13:32 thanks.
1:13:34 So,
1:13:35 Like one aspect that I think is
1:13:38 extremely important,
1:13:39 and I mean from
1:13:41 for economists that is kind of straightforward,
1:13:44 but I still think it is important to emphasize and
1:13:46 it's nice that it comes out of this kind of,
1:13:49 you know,
1:13:49 agnostic data driven kind of approach
1:13:52 that these price based instruments are,
1:13:55 if you like,
1:13:55 kind of an insurance that the other policies do not rebound.
1:14:00 So if you basically just put some subsidies or some building code,
1:14:04 etc.
1:14:05 to make the system more efficient,
1:14:06 then we know that.
1:14:07 Think of the transportation sector,
1:14:08 right,
1:14:08 like where we've seen that like large scale,
1:14:11 like probably also in the US I know more of the literature in Europe,
1:14:14 right?
1:14:15 Like basically we had those standards.
1:14:17 Cars got more efficient,
1:14:19 engines got more efficient,
1:14:20 etc.
1:14:20 like this.
1:14:21 But then
1:14:22 at the same time
1:14:23 actually cars just got.
1:14:25 Heavier and like in terms of fuel consumption and then he also emissions,
1:14:30 nothing actually happened.
1:14:31 And it changes if you in addition,
1:14:34 of course,
1:14:34 have a carbon price which then makes sure that those kind of instruments can also
1:14:39 kind of really work and do not kind of overflow.
1:14:42 So I think that is an extremely
1:14:44 important aspect
1:14:45 when it comes to these kind of um kind of policy stacking,
1:14:50 if you like.
1:14:51 And
1:14:52 another one is and this is was also mentioned by
1:14:55 Caroline,
1:14:56 I think that is kind of
1:14:58 different instruments even though they might target emissions,
1:15:02 they still might,
1:15:04 you know,
1:15:04 enable kind of specific policies to work.
1:15:07 So think of basically
1:15:09 kind of,
1:15:10 I didn't mention that,
1:15:11 but like part of the policy mix also was
1:15:14 kind of uh like in financing instruments in the finance sector.
1:15:19 So I think this is extremely important.
1:15:21 the role of alternatives
1:15:23 and like yeah,
1:15:25 alternatives need to be kind of financed and think of the electricity sector
1:15:28 right like it is straightforward basically we put a price on carbon,
1:15:32 the coal fired power plant gets more important
1:15:34 and countries might actually invest in more renewablesha but
1:15:39 actually the financing structure of renewables and coal looks very different
1:15:43 for renewables you have to finance everything upfront.
1:15:46 Uh,
1:15:47 whereas kind of for coal,
1:15:48 like a lot of the costs only occur sometime in the future,
1:15:51 that is in the fuel.
1:15:53 So now
1:15:54 in Europe,
1:15:55 like where we had uh probably the same in the US where we
1:15:59 have been actually in low interest environments for a long time,
1:16:02 this doesn't really matter.
1:16:04 But it matters if you actually have weighted average costs of capital that are 10,
1:16:08 15% as they are,
1:16:09 for example,
1:16:10 in Indonesia or Vietnam,
1:16:12 then kind of the effect of such a price
1:16:14 is
1:16:15 going to zero.
1:16:16 Uh,
1:16:17 if you don't have a parallel kind of a mechanism to de-risk
1:16:20 kind of those investments to kind of bring down the cost,
1:16:24 uh,
1:16:24 the financing costs,
1:16:25 etc.
1:16:26 So just as a specific example why I think
1:16:30 that there are these two things at the one side kind of prices
1:16:33 might enable kind of the efficiency of the other instruments to work.
1:16:37 And then there are,
1:16:37 however,
1:16:38 other kind of externalities if you like,
1:16:40 that are addressed by the policy mix.
1:16:43 Thank you again.
1:16:45 I think the point about cost of capital is extremely important.
1:16:49 In advanced economies,
1:16:51 cost of capital is around 4.5,
1:16:53 5% for renewables.
1:16:55 In middle-income economies,
1:16:56 it's close to 14%.
1:16:58 I think that's a huge
1:17:00 issue that's worth looking into.
1:17:02 Let me turn to you,
1:17:03 Barbara.
1:17:04 Um,
1:17:05 you
1:17:06 pretty much said
1:17:08 that carbon
1:17:09 offsetting is fundamentally flawed.
1:17:12 And so what's the implication
1:17:16 for mechanisms under Article 6 of the Paris Agreement,
1:17:20 which really rely a lot on these sort of offsets?
1:17:28 Yeah,
1:17:28 I think.
1:17:29 OK,
1:17:29 great.
1:17:30 Um,
1:17:30 yeah,
1:17:31 thanks for,
1:17:31 thanks for the question,
1:17:33 um.
1:17:35 Yeah,
1:17:35 I mean,
1:17:35 under,
1:17:36 under the Paris Agreement,
1:17:38 countries
1:17:39 took on uh uh NDCs a suite of suite of targets,
1:17:46 and the
1:17:48 Article 6 of the of the Paris Agreement allows for trading among countries
1:17:53 and several types of trading,
1:17:55 and countries don't
1:17:57 need to trade.
1:17:58 Many countries started off
1:18:01 by committing to
1:18:02 to targets that they would do domestically.
1:18:06 Um,
1:18:07 and
1:18:08 without
1:18:09 credits,
1:18:10 buying credits from other countries,
1:18:12 and
1:18:16 I think that that is a very positive way forward,
1:18:20 given
1:18:21 The quality challenges that we that we have seen to date
1:18:25 and also some real quality challenges,
1:18:27 challenges that we see with some decisions that have been
1:18:29 made so far under Article 6 of the Paris Agreement,
1:18:33 such as allowing in
1:18:36 old CDM credits
1:18:38 that meet certain characteristics,
1:18:40 the
1:18:41 total quantity of credits that are in line
1:18:45 and have requested transition from the CDM.
1:18:49 To the Paris Agreement equals around close to 1 billion tons.
1:18:53 That's huge.
1:18:54 Those are some of the projects that I,
1:18:56 that I studied,
1:18:57 you know,
1:18:58 15 years ago,
1:19:00 um,
1:19:00 and other and mostly other projects but that
1:19:03 follow very similar method very similar methodology.
1:19:07 More than half of those credits are hydropower
1:19:09 wind power projects and cook stoves credits,
1:19:11 so.
1:19:13 There we,
1:19:14 there we see the program
1:19:17 allowing in credits with very known quality issues.
1:19:24 So
1:19:26 Thank you for that.
1:19:26 And so,
1:19:27 I like also the point you said these offsets are creating a disincentive
1:19:32 to reduce emissions at home.
1:19:34 So that's,
1:19:34 that's a really important point.
1:19:36 Kaushik,
1:19:36 let me turn to you.
1:19:38 And
1:19:40 The Surat ETS has been successful.
1:19:43 But
1:19:45 It
1:19:46 takes a lot of capabilities among the institutions in the public
1:19:49 sector to be able to roll out such an ETS.
1:19:52 And
1:19:53 what are the conditions you think have really helped
1:19:57 to put this model to scale?
1:19:59 And what does it mean you have this long list of other countries you want to work on.
1:20:04 And other
1:20:05 places in India,
1:20:07 but they have
1:20:08 pretty weak governance and institutional capabilities.
1:20:11 So how do you think about rolling out such a program?
1:20:21 The whole idea of
1:20:23 creating this cap and trade scheme,
1:20:25 this emissions trading scheme in Surat,
1:20:27 and deploying that as a tool to deal with environmental issues there
1:20:31 was to prove the point
1:20:33 that you can use the
1:20:36 Sophisticated tool like a market-based instrument like a cap and trade scheme
1:20:41 in an environment with limited regulatory capacity and
1:20:45 still be able to achieve your environmental results
1:20:47 or overachieve or achieve environmental results in a much more effective fashion.
1:20:54 There's a certain tautology here.
1:20:57 Cap and trade schemes to deal with emission control
1:21:00 in developing countries
1:21:01 isn't a thing.
1:21:02 No one kind of usually has done this.
1:21:05 And because no one has ever done this,
1:21:07 you kind of don't have any evidence of this actually working or not working.
1:21:11 The Surat example essentially is one that establishes the fact
1:21:15 that the Gujarat Pollution Control Board
1:21:17 with our support
1:21:19 and the
1:21:20 use of
1:21:21 emissions control devices was able to roll out roll out an emissions trading scheme
1:21:25 that dealt with emissions on a 24/7 basis
1:21:28 without increasing
1:21:30 even a single employee
1:21:32 as staff.
1:21:35 The
1:21:36 point here is that to be able to deal with pollution and emissions
1:21:41 in this scale and in this particular sector,
1:21:44 the use of a cap and trade scheme is a much more effective solution than,
1:21:48 you know,
1:21:48 hiring more inspectors to be able to go and carry out more
1:21:51 stack testing and measuring emissions at the tailpipe
1:21:56 on a more regular and
1:21:58 continuous basis.
1:22:00 And that's exactly the point that doing this as a tool
1:22:05 across
1:22:05 countries and states with limited regulatory capacity
1:22:09 is a much more effective solution than actually kind of having
1:22:12 a larger suite of regulatory instruments.
1:22:16 I just also kind of wanted to quick uh respond to something that Carolyn said
1:22:20 in terms of,
1:22:21 uh,
1:22:22 I mean,
1:22:22 one thing that kind of
1:22:24 all of this calls for
1:22:26 is that you have to be very careful when you're designing the scheme.
1:22:29 And when we did design the scheme in Surat,
1:22:33 we grandfathered about 85% of the permits,
1:22:36 and 15% of the permits were
1:22:39 part of the initial permit allocation auction
1:22:42 where kind of firms participated and bought these permits.
1:22:45 The design of the scheme is such that this is not
1:22:49 this is not a mechanism for the government to earn more revenue,
1:22:53 so the government
1:22:54 or the pollution control board is not making money off the scheme,
1:22:57 unlike,
1:22:57 for instance,
1:22:58 would be the case with a
1:23:00 with a standard carbon pricing regime.
1:23:03 So that motivation we've kind of tried to eliminate so that that one.
1:23:08 One potential rent rent-seeking behavior that
1:23:11 you would see from government authorities
1:23:14 does not,
1:23:14 uh,
1:23:15 does not kind of corrupt the system in,
1:23:17 in that way.
1:23:20 You're very optimistic.
1:23:21 Ah
1:23:23 great.
1:23:23 So,
1:23:24 I would encourage whoever has to ask a question,
1:23:26 please come forward,
1:23:27 Govinda,
1:23:28 come to the mic.
1:23:29 Others just line up behind him,
1:23:31 and let's have a round of questions,
1:23:33 then we'll turn to the panel.
1:23:35 Yeah.
1:23:35 So I'm Govind Thima from the research department.
1:23:39 So I have one question for each of the panel members.
1:23:41 My first question is for Ian.
1:23:43 Ian,
1:23:43 you compare the different,
1:23:44 uh,
1:23:45 you know,
1:23:45 the ETS and carbon price,
1:23:47 uh,
1:23:48 you know,
1:23:48 instrument across the countries,
1:23:50 but the one challenge is that,
1:23:51 you know,
1:23:52 these instruments have a completely different design.
1:23:55 And the exposed estimation,
1:23:57 they have a completely different,
1:23:58 you know,
1:23:59 the efforts of the estimation technique they use.
1:24:02 So in that context,
1:24:04 what you have done to make them comparable,
1:24:06 that's one example that in South Africa,
1:24:08 they don't cover the electricity sector,
1:24:10 the main polluter,
1:24:11 the main emitter,
1:24:12 right?
1:24:12 So have you done anything to compare,
1:24:15 you know,
1:24:15 to make this,
1:24:16 you know,
1:24:18 instrument comparable?
1:24:19 That is my question.
1:24:20 Barbara,
1:24:21 uh,
1:24:21 so you,
1:24:22 your presentation is a little bit disappointing,
1:24:24 but,
1:24:24 you know,
1:24:25 if we see the CDM,
1:24:26 what you said,
1:24:27 you are right at the very beginning.
1:24:29 So I was in the,
1:24:30 you know,
1:24:30 this is the
1:24:31 registration issues team under the CDM,
1:24:34 uh,
1:24:34 Executive Board
1:24:35 from 2004 to 2007.
1:24:37 I evaluated 78 projects myself.
1:24:40 At the beginning,
1:24:41 there was an issue of the additionality because those projects might have,
1:24:44 you know,
1:24:44 implemented anyway,
1:24:46 but later on,
1:24:47 CDM has done a lot of contribution in a way that it gives a kind of the momentum.
1:24:51 For example,
1:24:52 for wind and solar.
1:24:54 There's a,
1:24:54 you know,
1:24:54 this type of incentive,
1:24:55 it gives a kind of the,
1:24:57 you know,
1:24:57 market
1:24:58 incentive for the,
1:24:59 you know,
1:24:59 different actors.
1:25:00 There's also innovation incentive,
1:25:02 you know,
1:25:02 incentive,
1:25:03 for example,
1:25:04 waste to energy,
1:25:05 and a lot of new projects come because of the CDM incentives.
1:25:08 I don't think,
1:25:09 you know,
1:25:09 if there's a new CDM,
1:25:11 those type of momentum on wind and solar,
1:25:14 and also those type of innovation
1:25:16 in terms of this other technology might have come,
1:25:18 you know,
1:25:19 that is.
1:25:20 So Prakai is a fantastic presentation and this is,
1:25:23 I think,
1:25:23 the first,
1:25:25 you know,
1:25:25 implementation of the market mechanism PM 2.5 right in Surat.
1:25:30 So you sure,
1:25:31 I mean,
1:25:31 it's a very good comparison because you know
1:25:34 for the implementation of noncompliance reduced to 1%,
1:25:38 but have you
1:25:39 seen any comparison between the cost?
1:25:41 So what is the cost of the regulatory measures versus the cost of
1:25:46 this emissions trading scheme over the?
1:25:49 So that is the question for you.
1:25:51 Thank you.
1:25:52 All right,
1:25:53 uh,
1:25:54 next,
1:25:54 please come in.
1:25:56 Hi,
1:25:56 I'm Elizabeth.
1:25:57 I work at JPal.
1:25:58 Um,
1:25:59 I was wondering how you might
1:26:01 use
1:26:02 Rachel Glenister's generalizability framework from 2017 to perhaps,
1:26:08 uh,
1:26:09 replicate
1:26:09 the SEAT success in the other countries.
1:26:16 Hello,
1:26:17 um,
1:26:18 I have a question for Barbara.
1:26:19 Barbara,
1:26:20 your research has been indeed instrumental in exposing
1:26:23 the systematic flaws in the offsetting markets,
1:26:27 especially on forest credits.
1:26:29 And the contribution model seems like something that might work better.
1:26:34 My question is,
1:26:36 how can we create incentives for companies to rely on these contribution models,
1:26:41 because
1:26:42 if they cannot claim the contributions against their
1:26:44 emission and we still live in a world where
1:26:47 Shareholders' value and
1:26:49 net zero are the currency that they are working with.
1:26:52 What incentives can be there and one step moving one step forward,
1:26:57 where will they find those authentic
1:27:00 carbon
1:27:01 reduction projects that they can contribute
1:27:05 and is there a way we can combine the offsetting with the contributions so
1:27:10 we we get to a better model than the one we are in?
1:27:13 Thank you.
1:27:14 And we have the last question.
1:27:17 Hi,
1:27:17 my name is Caroline.
1:27:18 I work at CGD and my question is for Barbara.
1:27:21 Um,
1:27:22 in your contributions work,
1:27:23 I'm just wondering if you can give some bullet points on how
1:27:27 that can go to rectify
1:27:28 these traditional issues with the BCM like such as
1:27:32 Um,
1:27:33 overcrediting,
1:27:33 leakage,
1:27:34 just curious,
1:27:35 and I'm sure it's maybe in some of your research that I haven't yet seen,
1:27:38 but
1:27:39 just want to know like how this
1:27:41 contributions like mindset shift can
1:27:44 start to affect that.
1:27:45 Thanks.
1:27:45 Thank you very much.
1:27:46 We're going to do the following.
1:27:47 We have,
1:27:48 we're almost out of time,
1:27:50 so I'll give each panelist a minute and a half
1:27:53 to either answer the questions or give your big picture takeaway.
1:27:57 And after that,
1:27:58 Carolyn,
1:27:59 you get 1 minute
1:28:00 to summarize.
1:28:03 All right,
1:28:03 Barbara,
1:28:04 start,
1:28:04 let's start with Barbara.
1:28:06 OK,
1:28:07 first thing,
1:28:08 I'm here for the week,
1:28:09 and I would be delighted to talk to you.
1:28:12 So,
1:28:12 um,
1:28:13 uh,
1:28:14 um,
1:28:16 find me,
1:28:17 um,
1:28:17 email me,
1:28:18 um,
1:28:19 so,
1:28:21 Uh
1:28:22 I think a lot of the questions are,
1:28:24 are,
1:28:24 are,
1:28:25 are really similar,
1:28:26 and that is
1:28:28 um
1:28:29 uh.
1:28:32 So,
1:28:33 I guess the first question on on additionality,
1:28:36 and that is,
1:28:36 I think often,
1:28:38 um,
1:28:40 Yes,
1:28:41 I mean,
1:28:41 the offset program has
1:28:44 created incentives to build some new projects.
1:28:46 It's also paid a lot of project developers to
1:28:49 build projects that they would have built anyway.
1:28:52 Um,
1:28:53 I think so often we think about offsets like a
1:28:56 way to generate climate finance for very worthwhile things,
1:29:01 and
1:29:03 we often forget about the trade
1:29:05 that those credits are being used by someone
1:29:08 to make a claim that they've reduced emissions.
1:29:11 And if the,
1:29:12 if it's an effective incentive,
1:29:15 but it's overcredited,
1:29:17 you actually can get an increase in global
1:29:19 emissions because someone is using those credits and
1:29:22 um
1:29:24 That's why I think a shift to the contributions approach can really
1:29:29 um
1:29:30 uh
1:29:32 match the way incentives really work like you
1:29:35 want to create effective incentive programs to support,
1:29:39 to support programs,
1:29:41 um,
1:29:42 recognizing that you're going to get non-additional projects,
1:29:45 recognizing um
1:29:47 that
1:29:48 funding is needed upfront.
1:29:50 And that if you shift to a contributions framework,
1:29:54 which refocuses attention on direct emissions reductions
1:29:57 because you aren't allowing that trade,
1:29:59 it creates
1:30:00 transparency and
1:30:02 what a company has done,
1:30:03 what a country has done and what they've purchased.
1:30:08 I think just
1:30:09 It's what it's a,
1:30:10 it's a claim,
1:30:11 it's words,
1:30:12 it's rhetoric,
1:30:13 but I think it has power
1:30:15 and I think just by disentangling
1:30:18 that claim
1:30:19 refocuses attention on direct emissions reductions
1:30:22 and then also it allows it opens up the possibility for
1:30:27 a range of projects,
1:30:28 including those that take into account many co-benefits,
1:30:31 including those that are
1:30:33 needed today in order to drive deep decarbonization
1:30:37 going forward.
1:30:38 And in terms of
1:30:40 where can we contribute?
1:30:42 How do we find those good projects,
1:30:44 there are so many amazing nonprofits,
1:30:47 amazing organizations,
1:30:49 governments with programs,
1:30:51 money is needed.
1:30:53 Right,
1:30:54 um,
1:30:55 and we need money going to the right places,
1:30:58 um,
1:30:59 so,
1:31:00 um,
1:31:00 I,
1:31:01 I envision sort of a movement towards direct contributions
1:31:05 to these organizations that have been working in the ground
1:31:07 for,
1:31:08 for a very long time and know,
1:31:11 have,
1:31:11 have,
1:31:12 uh,
1:31:12 uh,
1:31:12 uh,
1:31:13 are effectively able to support decarbonization
1:31:17 that answered some of the questions.
1:31:18 Thank you.
1:31:21 Yes,
1:31:21 thanks for your question.
1:31:22 Um,
1:31:23 yes,
1:31:24 we have.
1:31:24 Um,
1:31:26 basically,
1:31:26 we have actually
1:31:28 done some heterogeneity analysis,
1:31:31 like doing some Bayesian modeling analysis to really going
1:31:35 into the primary analysis and the primary studies and also
1:31:39 looking into secondary sources such as
1:31:42 World Bank to get a glance of the specific schemes
1:31:45 and then looking actually what is driving the heterogeneity.
1:31:49 Um,
1:31:50 and then indeed actually the,
1:31:53 the,
1:31:53 I haven't mentioned this,
1:31:54 but the difference in the specific study design
1:31:57 is kind of large.
1:31:59 So like all everything else equal kind of how a
1:32:01 study is actually done is also makes makes a difference.
1:32:04 But I,
1:32:05 we can also talk more about this uh offline because
1:32:08 it might get a bit nerdy if I continue.
1:32:10 Um,
1:32:11 on
1:32:12 um on the bigger picture,
1:32:14 I just wanted to
1:32:16 Kind of make one final comment which relates to one
1:32:19 of the last things that Kaushik said like in terms of
1:32:22 kind of to make actually sure
1:32:24 that the government doesn't have an incentive for rent seeking
1:32:27 because I think this is extremely important but based
1:32:30 on some theoretical work that we have been doing,
1:32:33 we can show that as soon as this actually Happens.
1:32:37 Basically,
1:32:38 the credibility of the uh of the possibility
1:32:40 of the government to have a time consistent,
1:32:43 credible
1:32:44 kind of um signal of this presence,
1:32:47 it just crumbles.
1:32:48 And then you have two options,
1:32:49 either you have prohibitive pricing or no pricing at all.
1:32:52 So as long as you can control this in the experiment,
1:32:55 it is fine.
1:32:56 I wonder whether it can always be controlled kind of out there in in the real world,
1:33:00 so to say.
1:33:01 Yeah,
1:33:02 and thank you.
1:33:02 I've been told by the organizers we're almost out of time,
1:33:06 so Kaushik will have the final word.
1:33:08 And then Carolyn,
1:33:09 we will hear from you.
1:33:11 Uh,
1:33:12 others can,
1:33:13 uh,
1:33:14 email her question,
1:33:15 your questions to her.
1:33:16 Sorry about that,
1:33:17 but Kaushik,
1:33:17 uh,
1:33:18 that's fine.
1:33:19 I only have a 17 minute speech more to go,
1:33:22 but,
1:33:23 but
1:33:24 I mean,
1:33:24 just kind of broadly to the point that.
1:33:27 This is
1:33:28 trying to use an economic instrument to solve for a particular problem.
1:33:32 So in this case,
1:33:32 this is a cap and trade scheme.
1:33:34 Uh,
1:33:34 we allocate some permits to grandfathering.
1:33:37 Some permits are bought in the initial allocation.
1:33:42 In the design of the market,
1:33:43 we kind of try and build in this case that at
1:33:46 the end of the compliance period whatever permits remain in the market
1:33:50 have to be bought back by the government.
1:33:52 So
1:33:53 there is,
1:33:54 so in the design of the scheme itself you kind of created a situation where
1:33:58 the government or the pollution regulator does not make money in this case.
1:34:02 But also in general when you kind of think about
1:34:05 using a tool like this,
1:34:07 you compare it with.
1:34:08 The alternative,
1:34:09 what is the cost of not doing this right
1:34:12 in a command and control regime,
1:34:14 the cost of polluting is infinite because you shut down,
1:34:20 and I mean,
1:34:21 for whatever it's worth,
1:34:21 economics tells you that everything has a cost,
1:34:24 everything has a price,
1:34:25 so.
1:34:27 Pollution,
1:34:28 CO2 emissions,
1:34:29 carbon,
1:34:30 they actually have a price
1:34:32 and that price is not infinity
1:34:34 because if it was infinity,
1:34:35 the solution would be to shut down all
1:34:37 economic activity that uses any kind of fossil fuel
1:34:40 and to get to that optimal price
1:34:43 is a question of having the right design
1:34:46 and the right structure that kind of delivers that particular outcome.
1:34:52 In designing this particular scheme,
1:34:54 we were kind of very,
1:34:54 very careful in terms of making sure that the
1:34:57 burden of cost
1:34:59 in designing the scheme sits with the industry,
1:35:02 and that's reflected in the cost-benefit ratio that's
1:35:04 kind of estimated in that one paper.
1:35:08 Thank you very much,
1:35:10 panelists.
1:35:10 That was fabulous.
1:35:12 Uh,
1:35:12 I think,
1:35:13 uh,
1:35:14 and thank you very much to the audience for being here till 6 p.m.
1:35:17 Uh,
1:35:18 we have an exciting day,
1:35:19 uh,
1:35:20 and a big round of applause for our panel.
1:35:25 Before we end for the day,
1:35:27 I would like to acknowledge
1:35:29 the amazing team who made ABCD happen.
1:35:32 Kenan Karakula is leading the team.
1:35:34 Please come over,
1:35:36 uh,
1:35:36 and,
1:35:36 and Indu and Carolina and Lisette,
1:35:39 and a big round of applause to them.
1:35:41 This wouldn't have happened without them.
1:35:44 And where is Joe and A?
1:35:48 All right,
1:35:48 thank you guys.
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A video recording of the Session 3 on Day 1 of The Annual Bank Conference on Development Economics 2025 "Development in the Age of Populism." This session discusses "Pollution".
CHAIR: Somik Lall, Senior Adviser in the Office of the World Bank Group Chief Economist and Director for Development Policy
PANELISTS:
Paper 1: Systemic Review and Meta-Analysis of Ex-Post Evaluations on the Effectiveness of Carbon Pricing (Jan Steckel, Brandenburg University of Technology)
➜ Presentation | ➜ Paper
Paper 2: Quality of Carbon Credit Projects and Alternative Methods to Finance Sequestration (Barbara Haya, University of California, Berkeley)
Paper 3: Can Pollution Markets Work in Developing Countries? Experimental Evidence from India (Kaushik Deb, The Energy Policy Institute at the University of Chicago's India Team)
➜ Presentation | ➜ Paper
DISCUSSANT: Carolyn Fischer, Lead Economist and Research Manager, Development Research Group, World Bank