Ceres

18 December, 2020

On 11 December 2020, Ceres, a sustainability nonprofit that works with investors on climate change, announced that a consortium of 30 investors managing $9 trillion in assets have committed to investing to support the goal of net zero carbon emissions by 2050.

This is what the 30 investors signed:

The Net Zero Asset Managers Commitment

In line with the best available science on the impacts of climate change, we acknowledge that there is an urgent need to accelerate the transition towards global net zero emissions and for asset managers to play our part to help deliver the goals of the Paris Agreement and ensure a just transition.

In this context, my organisation commits to support the goal of net zero greenhouse gas (‘GHG’) emissions by 2050, in line with global efforts to limit warming to 1.5°C (‘net zero emissions by 2050 or sooner’). It also commits to support investing aligned with net zero emissions by 2050 or sooner.

Specifically, my organisation commits to:

a) Work in partnership with asset owner clients on decarbonisation goals, consistent with an ambition to reach net zero emissions by 2050 or sooner across all assets under management (‘AUM’).
b) Set an interim target for the proportion of assets to be managed in line with the attainment of net zero emissions by 2050 or sooner.
c) Review our interim target at least every five years, with a view to ratcheting up the proportion of AUM covered until 100% of assets are included.

In order to fulfil these commitments my organisation will:

For assets committed to be managed in line with the attainment of net zero emissions by 2050 or sooner (under commitment b)

1) Set interim targets for 2030, consistent with a fair share of the 50% global reduction in CO2 identified as a requirement in the IPCC special report on global warming of 1.5°C.
2) Take account of portfolio Scope 1 & 2 emissions and, to the extent possible, material portfolio Scope 3 emissions.
3) Prioritise the achievement of real economy emissions reductions within the sectors and companies in which we invest.
4) If using offsets, invest in long-term carbon removal, where there are no technologically and/or financially viable alternatives to eliminate emissions.
5) As required, create investment products aligned with net zero emissions by 2050 and facilitate increased investment in climate solutions.

Across all assets under management

6) Provide asset owner clients with information and analytics on net zero investing and climate risk and opportunity.
7) Implement a stewardship and engagement strategy, with a clear escalation and voting policy, that is consistent with our ambition for all assets under management to achieve net zero emissions by 2050 or sooner.
8) Engage with actors key to the investment system including credit rating agencies, auditors, stock exchanges, proxy advisers, investment consultants, and data and service providers to ensure that products and services available to investors are consistent with the aim of achieving global net zero emissions by 2050 or sooner.
9) Ensure any relevant direct and indirect policy advocacy we undertake is supportive of achieving global net zero emissions by 2050 or sooner.

Accountability

10) Publish TCFD disclosures, including a climate action plan, annually, and submit them to the Investor Agenda via its partner organisations for review to ensure the approach applied is based on a robust methodology, consistent with the UN Race to Zero criteria, and action is being taken in line with the commitments made here.

We recognise collaborative investor initiatives including the Investor Agenda and its partner organisations (AIGCC, CDP, Ceres, IGCC, IIGCC, PRI, UNEPFI), Climate Action 100+, Climate League 2030, Paris Aligned Investment Initiative, Science Based Targets Initiative for Financial Institutions, UN-convened Net-Zero Asset Owner Alliance, among others, which are developing methodologies and supporting investors to take action towards net zero emissions. We will collaborate with each other and other investors via such initiatives so that investors have access to best practice, robust and science based approaches and standardised methodologies, and improved data, through which to deliver these commitments.

We also acknowledge that the scope for asset managers to invest for net zero and to meet the commitments set forth above depends on the mandates agreed with clients and clients’ and managers’ regulatory environments. These commitments are made in the expectation that governments will follow through on their own commitments to ensure the objectives of the Paris Agreement are met, including increasing the ambition of their Nationally Determined Contributions, and in the context of our legal duties to clients and unless otherwise prohibited by applicable law. In some asset classes or for some investment strategies, agreed net zero methodologies do not yet exist. Where our ability to align our approach to investment with the goal of net zero emissions by 2050 is, today, constrained, we commit to embark with determination and ambition on a journey, and to challenge and seek to overcome the constraints we face.


Shinise

2 December, 2020

 

The Japanese take pride in ‘shinise’: businesses that have lasted for hundreds or even thousands of years. This points out an interesting alternative to the goal of profit maximization: maximizing the time of survival.

• Ben Dooley and Hisako Ueno, This Japanese shop is 1,020 years old. It knows a bit about surviving crises, New York Times, 2 December 2020.

Such enterprises may be less dynamic than those in other countries. But their resilience offers lessons for businesses in places like the United States, where the coronavirus has forced tens of thousands into bankruptcy.

“If you look at the economics textbooks, enterprises are supposed to be maximizing profits, scaling up their size, market share and growth rate. But these companies’ operating principles are completely different,” said Kenji Matsuoka, a professor emeritus of business at Ryukoku University in Kyoto.

“Their No. 1 priority is carrying on,” he added. “Each generation is like a runner in a relay race. What’s important is passing the baton.”

Japan is an old-business superpower. The country is home to more than 33,000 with at least 100 years of history — over 40 percent of the world’s total. Over 3,100 have been running for at least two centuries. Around 140 have existed for more than 500 years. And at least 19 claim to have been continuously operating since the first millennium.

(Some of the oldest companies, including Ichiwa, cannot definitively trace their history back to their founding, but their timelines are accepted by the government, scholars and — in Ichiwa’s case — the competing mochi shop across the street.)

The businesses, known as “shinise,” are a source of both pride and fascination. Regional governments promote their products. Business management books explain the secrets of their success. And entire travel guides are devoted to them.

Of course if some businesses try to maximize time of survival, they may be small compared to businesses that are mainly trying to become “big”—at least if size is not the best road to long-term survival, which apparently it’s not. So we’ll have short-lived dinosaurs tromping around, and, dodging their footsteps, long-lived mice.

The idea of different organisms pursuing different strategies is familiar in ecology, where people talk about r-selected and K-selected organisms. The former “emphasize high growth rates, typically exploit less-crowded ecological niches, and produce many offspring, each of which has a relatively low probability of surviving to adulthood.” The latter “display traits associated with living at densities close to carrying capacity and typically are strong competitors in such crowded niches, that invest more heavily in fewer offspring, each of which has a relatively high probability of surviving to adulthood.”

But the contrast between r-selection and K-selection seems different to me than the contrast between profit maximization and lifespan maximization. As far as I know, no organism except humans deliberately tries to maximize the lifetime of anything.

And amusingly, the theory of r-selection versus K-selection may also be nearing the end of its life:

When Stearns reviewed the status of the theory in 1992, he noted that from 1977 to 1982 there was an average of 42 references to the theory per year in the BIOSIS literature search service, but from 1984 to 1989 the average dropped to 16 per year and continued to decline. He concluded that r/K theory was a once useful heuristic that no longer serves a purpose in life history theory.

For newer thoughts, see:

• D. Reznick, M. J. Bryant and F. Bashey, r-and K-selection revisited: the role of population regulation in life-history evolution, Ecology 83 (2002) 1509–1520.

See also:

• Innan Sasaki, How to build a business that lasts more than 200 years—lessons from Japan’s shinise companies, The Conversation, 6 June 2019.

Among other things, she writes:

We also found there to be a dark side to the success of these age-old shinise firms. At least half of the 17 companies we interviewed spoke of hardships in maintaining their high social status. They experienced peer pressure not to innovate (and solely focus on maintaining tradition) and had to make personal sacrifices to maintain their family and business continuity.

As the vice president of Shioyoshiken, a sweets company established in 1884, told us:

In a shinise, the firm is the same as the family. We need to sacrifice our own will and our own feelings and what we want to do … Inheriting and continuing the household is very important … We do not continue the business because we particularly like that industry. The fact that our family makes sweets is a coincidence. What is important is to continue the household as it is.

Innovations were sometimes discouraged by either the earlier family generation who were keen on maintaining the tradition, or peer shinise firms who cared about maintaining the tradition of the industry as a whole. Ultimately, we found that these businesses achieve such a long life through long-term sacrifice at both the personal and organisational level.


Exponential Discounting

25 October, 2020

Most of us seem to agree that the promise of a dollar in the future is worth less to us than a dollar today, even if the promise is certain to be fulfilled. Economists often assume ‘exponential discounting’, which says that a dollar promised at some time s is worth

\exp(-\alpha(s - t))

dollars in hand at time t. The constant \alpha is connected to the ‘interest rate’.

Why are economists so wedded to exponential discounting? The main reason is probably that it’s mathematically simple. But one argument for it goes roughly like this: if your decisions today are to look rational at any future time, you need to use exponential discounting.

In practice, humans, pigeons and rats do not use exponential discounting. So, economists say they are ‘dynamically inconsistent’:

• Wikipedia, Dynamic inconsistency.

In economics, dynamic inconsistency or time inconsistency is a situation in which a decision-maker’s preferences change over time in such a way that a preference can become inconsistent at another point in time. This can be thought of as there being many different “selves” within decision makers, with each “self” representing the decision-maker at a different point in time; the inconsistency occurs when not all preferences are aligned.

I this ‘inconsistent’ could be a misleading term for what’s going on here. It suggests that something bad is happening. That may not be true.

Anyway, some of the early research on this was done by George Ainslie, and here is what he found:

Ainslie’s research showed that a substantial number of subjects reported that they would prefer $50 immediately rather than $100 in six months, but would NOT prefer $50 in 3 months rather than $100 in nine months, even though this was the same choice seen at 3 months’ greater distance. More significantly, those subjects who said they preferred $50 in 3 months to $100 in 9 months said they would NOT prefer $50 in 12 months to $100 in 18 months—again, the same pair of options at a different distance—showing that the preference-reversal effect did not depend on the excitement of getting an immediate reward. Nor does it depend on human culture; the first preference reversal findings were in rats and pigeons.

Let me give a mathematical argument for exponential discounting. Of course it will rely on some assumptions. I’m not claiming these assumptions are true! Far from it. I’m just claiming that if we don’t use exponential discounting, we are violating one or more of these assumptions… or breaking out of the whole framework of my argument. The widespread prevalence of ‘dynamic inconsistency’ suggests that the argument doesn’t apply to real life.

Here’s the argument:

Suppose the value to us at any time t of a dollar given to us at some other time s is V(t,s).

Let us assume:

1) The ratio

\displaystyle{ \frac{V(t,s_2)}{V(t,s_1)} }

is independent of t. E.g., the ratio of value of a “dollar on Friday” to “a dollar on Thursday” is the same if you’re computing it on Monday, or on Tuesday, or on Wednesday.

2) The quantity V(t,s) depends only on the difference s - t.

3) The quantity V(t,s) is a continuous function of s and t.

Then we can show

V(t,s) = k \exp(-\alpha(s-t))

for some constants \alpha and k. Typically we assume k = 1 since the value of a dollar given to us right now is 1. But let’s just see how we get this formula for V(t,s) out of assumptions 1), 2) and 3).

The proof goes like this. By 2) we know

V(t,s) = F(s-t)

for some function F. By 1) it follows that

\displaystyle{ \frac{F(s_2 - t)}{F(s_1 - t)} }

is independent of t, so

\displaystyle{ \frac{F(s_2 - t)}{F(s_1 - t)} =  \frac{F(s_2)}{F(s_1)} }

or in other words

F(s_2 - t) F(s_1) = F(s_2) F(s_1 - t)

Ugh! What next? Well, if we take s_1 = t, we get a simpler equation that’s probably still good enough to get the job done:

F(s_2 - t) F(t) = F(s_2) F(0)

Now let’s make up a variable t' = s_2 - t, so that s_2 = t + t'. Then we can rewrite our equation as

F(t') F(t) = F(t+t') F(0)

or

F(t) F(t') = F(t+t') F(0)

This is beautiful except for the constant F(0). Let’s call that k and factor it out by writing

F(t) = k G(t)

Then we get

G(t) G(t') = G(t+t')

A theorem of Cauchy implies that any continuous solution of this equation is of the form

G(t) = \exp(-\alpha t)

So, we get

F(t) = k \exp(-\alpha t)

or

V(t,s) = k \exp(-\alpha(s-t))

as desired!

By the way, we don’t need to assume G is continuous: it’s enough to assume G is measurable. You can get bizarre nonmeasurable solutions of G(t) G(t') = G(t+t') using the axiom of choice, but they are not of practical interest.

So, assumption 3) is not the assumption I’d want to attack in trying to argue against exponential discounting. In fact both assumptions 1) and 2) are open to quite a few objections. Can you name some? Here’s one: in real life the interest rate changes with time. There must be some reason.

By the way, nothing in the argument I gave shows that \alpha \ge 0. So there could be people who obey assumptions 1)–3) yet believe the promise of a dollar in the future is worth more than a dollar in hand today.

Also, nothing in my argument for the form of V(t,s) assumes that s \ge t. That is, my assumptions as stated also concern the value of a dollar that was promised in the past. So, you might have fun seeing what changes, or does not change, if you restrict the assumptions to say they only apply when s \ge t. The arrow of time seems to be built into economics, after all.

Also, you may enjoy finding the place in my derivation where I might have divided by zero, and figure out to do about that.

If you don’t like exponential discounting—for example, because people use it to argue against spending money now to fight climate change—you might prefer hyperbolic discounting:

• Wikipedia, Hyperbolic discounting.


Compositional Game Theory and Climate Microeconomics

5 October, 2020

guest post by Jules Hedges

Hi all

This is a post I’ve been putting off for a long time until I was sure I was ready. I am the “lead developer” of a thing called compositional game theory (CGT). It’s an approach to game theory based on category theory, but we are now at the point where you don’t need to know that anymore: it’s an approach to game theory that has certain specific benefits over the traditional approach.

I would like to start a conversation about “using my powers for good”. I am hoping particularly that it is possible to model microeconomic aspects of climate science. This seems to be a very small field and I’m not really hopeful that anyone on Azimuth will have the right background, but it’s worth a shot. The kind of thing I’m imagining (possibly completely wrongly) is to create models that will suggest when a technically-feasible solution is not socially feasible. Social dilemmas and tragedies of the commons are at the heart of the climate crisis, and modelling instances of them is in scope.

I have a software tool (https://github.com/jules-hedges/open-games-hs) that is designed to be an assistant for game-theoretic modelling. This I can’t emphasise enough: A human with expertise in game-theoretic modelling is the most important thing, CGT is merely an assistant. (Right now the tool also probably can’t be used without me being in the loop, but that’s not an inherent thing.)

To give an idea what sort of things CGT can do, my 2 current ongoing research collaborations are: (1) a social science project modelling examples of institution governance, and (2) a cryptoeconomics project modelling an attack against a protocol using bribes. On a technical level the best fit is for Bayesian games, which are finite-horizon, have common knowledge priors, and private knowledge with agents who do Bayesian updating.

A lot of the (believed) practical benefits of CGT come from the fact that the model is code (in a high level language designed specifically for expressing games) and thus the model can be structured according to existing wisdom for structuring code. Really stress-testing this claim is an ongoing research project. My tool does equilibrium-checking for all games (the technical term is “model checker”), and we’ve had some success doing other things by looping an equilibrium check over a parameter space. It makes no attempt to be an equilibrium solver, that is left for the human.

This is not me trying to push my pet project (I do that elsewhere) but me trying to find a niche where I can do some genuine good, even if small. If you are a microeconomist (or a social scientist who uses applied game theory) and share the goals of Azimuth, I would like to hear from you, even if it’s just for some discussion.


Diary, 2003-2020

8 August, 2020

I keep putting off organizing my written material, but with coronavirus I’m feeling more mortal than usual, so I’d like get this out into the world now:

• John Baez, Diary, 2003–2020.

Go ahead and grab a copy!

It’s got all my best tweets and Google+ posts, mainly explaining math and physics, but also my travel notes and other things… starting in 2003 with my ruminations on economics and ecology. It’s too big to read all at once, but I think you can dip into it more or less anywhere and pull out something fun.

It goes up to July 2020. It’s 2184 pages long.

I fixed a few problems like missing pictures, but there are probably more. If you let me know about them, I’ll fix them (if it’s easy).


Vaclav Smil on Growth

22 September, 2019

Yet another interesting book I haven’t read yet:

• Vaclav Smil, Growth: From Microorganisms to Megacities, MIT Press, Cambridge, 2019.

As I hope you know, Vaclav Smil is an expert on energy, food, population, and economics, who assembles and analyzes data in fact-filled books like Energy and Civilization: a History.  Bill Gates has said “I wait for new Smil books the way some people wait for the next ‘Star Wars’ movie.”

He was interviewed here:

• Jonathan Watts, Vaclav Smil: ‘Growth must end. Our economist friends don’t seem to realise that’, 21 September 2019.

The interview begins:

You are the nerd’s nerd. There is perhaps no other academic who paints pictures with numbers like you. You dug up the astonishing statistic that China has poured more cement every three years since 2003 than the US managed in the entire 20th century. You calculated that in 2000, the dry mass of all the humans in the world was 125m metric tonnes compared with just 10m tonnes for all wild vertebrates. And now you explore patterns of growth, from the healthy development of forests and brains to the unhealthy increase in obesity and carbon dioxide in the atmosphere. Before we get into those deeper issues, can I ask if you see yourself as a nerd?

The facts here are fascinating but the question is absurd. Are we really sinking into such anti-intellectualism that a journalist feels the need to start a conversation with a scientist by asking if he sees himself as a “nerd”?

I’d have been tempted to reply “First, can I ask if you see yourself as a twit?” Smil more wisely replied:

Not at all. I’m just an old-fashioned scientist describing the world and the lay of the land as it is. That’s all there is to it.

Here’s why he wrote the book:

I have deliberately set out to write the megabook on growth. In a way, it’s unwieldy and unreasonable. People can take any number of books out of it–economists can read about the growth of GDP and population; biologists can read about the growth of organisms and human bodies. But I wanted to put it all together under one roof so people could see how these things are inevitably connected and how it all shares one crystal clarity: that growth must come to an end. Our economist friends don’t seem to realise that.

He advocates degrowth in some places… but growth in others:

[…] it’s important not to talk in global terms. There will be many approaches which have to be tailored and targeted to each different audience. There is this pernicious idea by this [Thomas] Friedman guy that the world is flat and everything is now the same, so what works in one place can work for everyone. But that’s totally wrong. For example, Denmark has nothing in common with Nigeria. What you do in each place will be different. What we need in Nigeria is more food, more growth. In Philippines we need a little more of it. And in Canada and Sweden, we need less of it. We have to look at it from different points of view. In some places we have to foster what economists call de-growth. In other places, we have to foster growth.

I’m sure his book will be more interesting than these quotes, because it’ll be full of well-organized and important facts—and the questions surrounding growth are some of the most pressing of our age.


Divesting

18 September, 2019

Christian Williams

John always tells me to write short, sweet, and clear. Knowing that his advice is supreme on these matters, I’ll try to write mini-posts in between the bigger ones. But… not this time – the topic is too good.

(Dispossess of property/authority. Say it, sound smart.)

…..

Work smarter, not (just) harder.

Today I got an email from Bill McKibben, founder of 350.org. (350 parts per million, the concentration of CO2 considered a “safe upper limit” for Earth, by NASA scientists James Hansen. We’re soaring past 415ppm.) In preparation for the global climate strike, Bill wants to share an important idea: divesting from fossil fuels may be our greatest lever.

Money is the Oxygen on which the Fire of Global Warming Burns

I’ll pluck paragraphs to quote, but please read the whole article; this is an extremely important and practical idea for addressing the crisis. And it’s well written… the first sentence sounds fairly Baezian.

I’m skilled at eluding the fetal crouch of despair—because I’ve been working on climate change for thirty years, I’ve learned to parcel out my angst, to keep my distress under control. But, in the past few months, I’ve more often found myself awake at night with true fear-for-your-kids anguish. This spring, we set another high mark for carbon dioxide in the atmosphere: four hundred and fifteen parts per million, higher than it has been in many millions of years. The summer began with the hottest June ever recorded, and then July became the hottest month ever recorded. The United Kingdom, France, and Germany, which have some of the world’s oldest weather records, all hit new high temperatures, and then the heat moved north, until most of Greenland was melting and immense Siberian wildfires were sending great clouds of carbon skyward. At the beginning of September, Hurricane Dorian stalled above the Bahamas, where it unleashed what one meteorologist called “the longest siege of violent, destructive weather ever observed” on our planet.

Bill emphasizes that change has moved far too slowly, of course. But he’s spent the past week with Greta Thunberg and many other activists, and one can tell that he really is heartened.

It seems that there are finally enough people to make an impact… what if there were an additional lever to pull, one that could work both quickly and globally?

The answer: money.

Today it is large corporations which have the greatest power over daily life, and they are far more susceptible to pressure and change then the insulated bureaucracies of governments.

Thankfully Bill and many others knew this years ago, and started a divestment campaign of breathtaking magnitude:

Seven years ago, 350.org helped launch a global movement to persuade the managers of college endowments, pension funds, and other large pots of money to sell their stock in fossil-fuel companies. It has become the largest such campaign in history: funds worth more than eleven trillion dollars have divested some or all of their fossil-fuel holdings.

$11,000,000,000,000.

And it has been effective: when Peabody Energy, the largest American coal company, filed for bankruptcy, in 2016, it cited divestment as one of the pressures weighing on its business, and, this year, Shell called divestment a “material adverse effect” on its performance.

The movement is only growing, accelerating, and setting its sights on the big gorillas. The main sectors: banking, asset management, and insurance.

Consider a bank like, say, JPMorgan Chase, which is America’s largest bank and the world’s most valuable by market capitalization. In the three years since the end of the Paris climate talks, Chase has reportedly committed 196 billion dollars in financing for the fossil-fuel industry, much of it to fund extreme new ventures: ultra-deep-sea drilling, Arctic oil extraction, and so on. In each of those years, ExxonMobil, by contrast, spent less than 3 billion dollars on exploration, research, and development. $196B is larger than the market value of BP; it dwarfs that of the coal companies or the frackers. By this measure, Jamie Dimon, the C.E.O. of JPMorgan Chase, is an oil, coal, and gas baron almost without peer.


But here’s the thing: fossil-fuel financing accounts for only about 7% of Chase’s lending and underwriting. The bank lends to everyone else, too—to people who build bowling alleys and beach houses and breweries. And, if the world were to switch decisively to solar and wind power, Chase would lend to renewable-energy companies, too. Indeed, it already does, though on a much smaller scale… It’s possible to imagine these industries, given that the world is now in existential danger, quickly jettisoning their fossil-fuel business. It’s not easy to imagine—capitalism is not noted for surrendering sources of revenue. But, then, the Arctic ice sheet is not noted for melting.

Bill elucidates the fact that it is critical to effect the divestment of giants like Chase, Blackrock, and Chubb. Even if these targets are quite hard, this method of action applies to every aspect of the economy, and empowers every single individual (more below). If the total divestment is spread over a decade, it can be done without serious economic instability. And if done well, it will spur tremendous growth in the renewable energy sector and ecological economy in general, as public consciousness opens up to these ideas on a large scale.

I want to keep giving quotes, but you can read it. (If anyone is out of free articles for New Yorker, I can send a text file.) I’ll contribute a few of my own thoughts, expanding on stuff implicit in the article; and then this topic can be continued with another post.

…..

Divesting is a truly powerful lever, for several reasons.

First, money talks. Many people who have been misled by modern society have the following equation in their heads:

money = value

These people, being overwhelmed with social complexity, have lifted the “burden” of large-scale ethics off of their shoulders and into a blind faith in the economic system – thinking “well, if enough people have the right idea, then capitalism will surely head in the right direction.”

Of course, after not too long, we find that this is not the case. But their thinking has not changed, and we need a way to communicate with them. While it may feel strange and wrong to reformulate the message from “ethical imperative” to “financial risk”, this is the way to get through to many people in powerful places. When you read about success stories, it is effective, especially considering all the time spent mired in anthropogenic-warming skepticism.

Second, social pressure is now a real force in the world. We can bend competition to our will: incentivize companies to better practices, and when one capitulates, the others in that sphere follow. It has happened many times, and the current is only getting stronger.

Though if we want to fry bigger fish than no-straws, we need to sharpen our collective tactics. It will of course be more systematic and penetrating than shaming companies on Twitter. The article includes great examples of this; it would be awesome to discuss more ideas in the comments.

Third, everyone can help this way, directly and significantly. Everyone has a bank account. It is not difficult, nor seriously detrimental, to switch to a credit union. The divestment campaign can be significantly accelerated by a movement of concerned citizens making this transition.

(My family uses Chase. When I was spending quality time back home, I asked my parents how the value of a bank is anything more than secure money storage. The main thing they mentioned was loans – but they admitted that the biggest and best loan they ever took was through a credit union. The reasons simply did not add up. I plan to show them this article, and I’ll try to have an earnest conversation with them. I really hope they understand, because I know they are rational and good people.)

It’s all but impossible for most of us to stop using fossil fuels immediately, especially since, in many places, the fossil-fuel and utility industries have made it difficult and expensive to install solar panels on your roof. But it’s both simple and powerful to switch your bank account: local credit unions and small-town banks are unlikely to be invested in fossil fuels, and Beneficial State Bank and Amalgamated Bank bring fossil-free services to the West and East Coasts, respectively, while Aspiration Bank offers them online. (And they’re all connected to A.T.M.s.)


This all could, in fact, become one of the final great campaigns of the climate movement—a way to focus the concerted power of any person, city, and institution with a bank account, a retirement fund, or an insurance policy on the handful of institutions that could actually change the game. We are indeed in a climate moment—people’s fear is turning into anger, and that anger could turn fast and hard on the financiers. If it did, it wouldn’t end the climate crisis: we still have to pass the laws that would actually cut the emissions, and build out the wind farms and solar panels. Financial institutions can help with that work, but their main usefulness lies in helping to break the power of the fossil-fuel companies.

…..

The economy is far more responsive to changes in the collective ethos than the government. This is how people can directly express their values every day, with every bit of earning they have. We are recognizing that the public mindset is changing, and we can now take heart and leverage society in the right direction.

Conjecture The critical science of our time has the form:

Ecology
\Uparrow \;\;\;\;\; \Downarrow
Economy

This is why John Baez brought together so many capable people for the Azimuth Project. I hope that we can connect with the new momentum and coordinate on something great. Even in just the last post there were some really good ideas. I really look forward to hearing more. Thanks.


Correlated Equilibria in Game Theory

24 July, 2017

Erica Klarreich is one of the few science journalists who explains interesting things I don’t already know clearly enough so I can understand them. I recommend her latest article:

• Erica Klarreich, In game theory, no clear path to equilibrium, Quanta, 18 July 2017.

Economists like the concept of ‘Nash equilibrium’, but it’s problematic in some ways. This matters for society at large.

In a Nash equilibrium for a multi-player game, no player can improve their payoff by unilaterally changing their strategy. This doesn’t mean everyone is happy: it’s possible to be trapped in a Nash equilibrium where everyone is miserable, because anyone changing their strategy unilaterally would be even more miserable. (Think ‘global warming’.)

The great thing about Nash equilibria is that their meaning is easy to fathom, and they exist. John Nash won a Nobel prize for a paper proving that they exist. His paper was less than one page long. But he proved the existence of Nash equilibria for arbitrary multi-player games using a nonconstructive method: a fixed point theorem that doesn’t actually tell you how to find the equilibrium!

Given this, it’s not surprising that Nash equilibria can be hard to find. Last September a paper came out making this precise, in a strong way:

• Yakov Babichenko and Aviad Rubinstein, Communication complexity of approximate Nash equilibria.

The authors show there’s no guaranteed method for players to find even an approximate Nash equilibrium unless they tell each other almost everything about their preferences. This makes finding the Nash equilibrium prohibitively difficult to find when there are lots of players… in general. There are particular games where it’s not difficult, and that makes these games important: for example, if you’re trying to run a government well. (A laughable notion these days, but still one can hope.)

Klarreich’s article in Quanta gives a nice readable account of this work and also a more practical alternative to the concept of Nash equilibrium. It’s called a ‘correlated equilibrium’, and it was invented by the mathematician Robert Aumann in 1974. You can see an attempt to define it here:

• Wikipedia, Correlated equilibrium.

The precise mathematical definition near the start of this article is a pretty good example of how you shouldn’t explain something: it contains a big fat equation containing symbols not mentioned previously, and so on. By thinking about it for a while, I was able to fight my way through it. Someday I should improve it—and someday I should explain the idea here! But for now, I’ll just quote this passage, which roughly explains the idea in words:

The idea is that each player chooses their action according to their observation of the value of the same public signal. A strategy assigns an action to every possible observation a player can make. If no player would want to deviate from the recommended strategy (assuming the others don’t deviate), the distribution is called a correlated equilibrium.

According to Erica Klarreich it’s a useful notion. She even makes it sound revolutionary:

This might at first sound like an arcane construct, but in fact we use correlated equilibria all the time—whenever, for example, we let a coin toss decide whether we’ll go out for Chinese or Italian, or allow a traffic light to dictate which of us will go through an intersection first.

In [some] examples, each player knows exactly what advice the “mediator” is giving to the other player, and the mediator’s advice essentially helps the players coordinate which Nash equilibrium they will play. But when the players don’t know exactly what advice the others are getting—only how the different kinds of advice are correlated with each other—Aumann showed that the set of correlated equilibria can contain more than just combinations of Nash equilibria: it can include forms of play that aren’t Nash equilibria at all, but that sometimes result in a more positive societal outcome than any of the Nash equilibria. For example, in some games in which cooperating would yield a higher total payoff for the players than acting selfishly, the mediator can sometimes beguile players into cooperating by withholding just what advice she’s giving the other players. This finding, Myerson said, was “a bolt from the blue.”

(Roger Myerson is an economics professor at the University of Chicago who won a Nobel prize for his work on game theory.)

And even though a mediator can give many different kinds of advice, the set of correlated equilibria of a game, which is represented by a collection of linear equations and inequalities, is more mathematically tractable than the set of Nash equilibria. “This other way of thinking about it, the mathematics is so much more beautiful,” Myerson said.

While Myerson has called Nash’s vision of game theory “one of the outstanding intellectual advances of the 20th century,” he sees correlated equilibrium as perhaps an even more natural concept than Nash equilibrium. He has opined on numerous occasions that “if there is intelligent life on other planets, in a majority of them they would have discovered correlated equilibrium before Nash equilibrium.”

When it comes to repeated rounds of play, many of the most natural ways that players could choose to adapt their strategies converge, in a particular sense, to correlated equilibria. Take, for example, “regret minimization” approaches, in which before each round, players increase the probability of using a given strategy if they regret not having played it more in the past. Regret minimization is a method “which does bear some resemblance to real life — paying attention to what’s worked well in the past, combined with occasionally experimenting a bit,” Roughgarden said.

(Tim Roughgarden is a theoretical computer scientist at Stanford University.)

For many regret-minimizing approaches, researchers have shown that play will rapidly converge to a correlated equilibrium in the following surprising sense: after maybe 100 rounds have been played, the game history will look essentially the same as if a mediator had been advising the players all along. It’s as if “the [correlating] device was somehow implicitly found, through the interaction,” said Constantinos Daskalakis, a theoretical computer scientist at the Massachusetts Institute of Technology.

As play continues, the players won’t necessarily stay at the same correlated equilibrium — after 1,000 rounds, for instance, they may have drifted to a new equilibrium, so that now their 1,000-game history looks as if it had been guided by a different mediator than before. The process is reminiscent of what happens in real life, Roughgarden said, as societal norms about which equilibrium should be played gradually evolve.

In the kinds of complex games for which Nash equilibrium is hard to reach, correlated equilibrium is “the natural leading contender” for a replacement solution concept, Nisan said.

As Klarreich hints, you can find correlated equilibria using a technique called linear programming. That was proved here, I think:

• Christos H. Papadimitriou and Tim Roughgarden, Computing correlated equilibria in multi-player games, J. ACM 55 (2008), 14:1-14:29.

Do you know something about correlated equilibria that I should know? If so, please tell me!


Complexity Theory and Evolution in Economics

24 April, 2017

This book looks interesting:

• David S. Wilson and Alan Kirman, editors, Complexity and Evolution: Toward a New Synthesis for Economics, MIT Press, Cambridge Mass., 2016.

You can get some chapters for free here. I’ve only looked carefully at this one:

• Joshua M. Epstein and Julia Chelen, Advancing Agent_Zero.

Agent_Zero is a simple toy model of an agent that’s not the idealized rational actor often studied in economics: rather, it has emotional, deliberative, and social modules which interact with each other to make decisions. Epstein and Chelen simulate collections of such agents and see what they do:

Abstract. Agent_Zero is a mathematical and computational individual that can generate important, but insufficiently understood, social dynamics from the bottom up. First published by Epstein (2013), this new theoretical entity possesses emotional, deliberative, and social modules, each grounded in contemporary neuroscience. Agent_Zero’s observable behavior results from the interaction of these internal modules. When multiple Agent_Zeros interact with one another, a wide range of important, even disturbing, collective dynamics emerge. These dynamics are not straightforwardly generated using the canonical rational actor which has dominated mathematical social science since the 1940s. Following a concise exposition of the Agent_Zero model, this chapter offers a range of fertile research directions, including the use of realistic geographies and population levels, the exploration of new internal modules and new interactions among them, the development of formal axioms for modular agents, empirical testing, the replication of historical episodes, and practical applications. These may all serve to advance the Agent_Zero research program.

It sounds like a fun and productive project as long as one keeps ones wits about one. It’s hard to draw conclusions about human behavior from such simplified agents. One can argue about this, and of course economists will. But regardless of this, one can draw conclusions about which kinds of simplified agents will engage in which kinds of collective behavior under which conditions.

Basically, one can start mapping out a small simple corner of the huge ‘phase space’ of possible societies. And that’s bound to lead to interesting new ideas that one wouldn’t get from either 1) empirical research on human and animal societies or 2) pure theoretical pondering without the help of simulations.

Here’s an article whose title, at least, takes a vastly more sanguine attitude toward benefits of such work:

• Kate Douglas, Orthodox economics is broken: how evolution, ecology, and collective behavior can help us avoid catastrophe, Evonomics, 22 July 2016.

I’ll quote just a bit:

For simplicity’s sake, orthodox economics assumes that Homo economicus, when making a fundamental decision such as whether to buy or sell something, has access to all relevant information. And because our made-up economic cousins are so rational and self-interested, when the price of an asset is too high, say, they wouldn’t buy—so the price falls. This leads to the notion that economies self-organise into an equilibrium state, where supply and demand are equal.

Real humans—be they Wall Street traders or customers in Walmart—don’t always have accurate information to hand, nor do they act rationally. And they certainly don’t act in isolation. We learn from each other, and what we value, buy and invest in is strongly influenced by our beliefs and cultural norms, which themselves change over time and space.

“Many preferences are dynamic, especially as individuals move between groups, and completely new preferences may arise through the mixing of peoples as they create new identities,” says anthropologist Adrian Bell at the University of Utah in Salt Lake City. “Economists need to take cultural evolution more seriously,” he says, because it would help them understand who or what drives shifts in behaviour.

Using a mathematical model of price fluctuations, for example, Bell has shown that prestige bias—our tendency to copy successful or prestigious individuals—influences pricing and investor behaviour in a way that creates or exacerbates market bubbles.

We also adapt our decisions according to the situation, which in turn changes the situations faced by others, and so on. The stability or otherwise of financial markets, for instance, depends to a great extent on traders, whose strategies vary according to what they expect to be most profitable at any one time. “The economy should be considered as a complex adaptive system in which the agents constantly react to, influence and are influenced by the other individuals in the economy,” says Kirman.

This is where biologists might help. Some researchers are used to exploring the nature and functions of complex interactions between networks of individuals as part of their attempts to understand swarms of locusts, termite colonies or entire ecosystems. Their work has provided insights into how information spreads within groups and how that influences consensus decision-making, says Iain Couzin from the Max Planck Institute for Ornithology in Konstanz, Germany—insights that could potentially improve our understanding of financial markets.

Take the popular notion of the “wisdom of the crowd”—the belief that large groups of people can make smart decisions even when poorly informed, because individual errors of judgement based on imperfect information tend to cancel out. In orthodox economics, the wisdom of the crowd helps to determine the prices of assets and ensure that markets function efficiently. “This is often misplaced,” says Couzin, who studies collective behaviour in animals from locusts to fish and baboons.

By creating a computer model based on how these animals make consensus decisions, Couzin and his colleagues showed last year that the wisdom of the crowd works only under certain conditions—and that contrary to popular belief, small groups with access to many sources of information tend to make the best decisions.

That’s because the individual decisions that make up the consensus are based on two types of environmental cue: those to which the entire group are exposed—known as high-correlation cues—and those that only some individuals see, or low-correlation cues. Couzin found that in larger groups, the information known by all members drowns out that which only a few individuals noticed. So if the widely known information is unreliable, larger groups make poor decisions. Smaller groups, on the other hand, still make good decisions because they rely on a greater diversity of information.

So when it comes to organising large businesses or financial institutions, “we need to think about leaders, hierarchies and who has what information”, says Couzin. Decision-making structures based on groups of between eight and 12 individuals, rather than larger boards of directors, might prevent over-reliance on highly correlated information, which can compromise collective intelligence. Operating in a series of smaller groups may help prevent decision-makers from indulging their natural tendency to follow the pack, says Kirman.

Taking into account such effects requires economists to abandon one-size-fits-all mathematical formulae in favour of “agent-based” modelling—computer programs that give virtual economic agents differing characteristics that in turn determine interactions. That’s easier said than done: just like economists, biologists usually model relatively simple agents with simple rules of interaction. How do you model a human?

It’s a nut we’re beginning to crack. One attendee at the forum was Joshua Epstein, director of the Center for Advanced Modelling at Johns Hopkins University in Baltimore, Maryland. He and his colleagues have come up with Agent_Zero, an open-source software template for a more human-like actor influenced by emotion, reason and social pressures. Collections of Agent_Zeros think, feel and deliberate. They have more human-like relationships with other agents and groups, and their interactions lead to social conflict, violence and financial panic. Agent_Zero offers economists a way to explore a range of scenarios and see which best matches what is going on in the real world. This kind of sophistication means they could potentially create scenarios approaching the complexity of real life.

Orthodox economics likes to portray economies as stately ships proceeding forwards on an even keel, occasionally buffeted by unforeseen storms. Kirman prefers a different metaphor, one borrowed from biology: economies are like slime moulds, collections of single-celled organisms that move as a single body, constantly reorganising themselves to slide in directions that are neither understood nor necessarily desired by their component parts.

For Kirman, viewing economies as complex adaptive systems might help us understand how they evolve over time—and perhaps even suggest ways to make them more robust and adaptable. He’s not alone. Drawing analogies between financial and biological networks, the Bank of England’s research chief Andrew Haldane and University of Oxford ecologist Robert May have together argued that we should be less concerned with the robustness of individual banks than the contagious effects of one bank’s problems on others to which it is connected. Approaches like this might help markets to avoid failures that come from within the system itself, Kirman says.

To put this view of macroeconomics into practice, however, might mean making it more like weather forecasting, which has improved its accuracy by feeding enormous amounts of real-time data into computer simulation models that are tested against each other. That’s not going to be easy.

 


The Price of Everything

29 February, 2016

Astronomers using the Hubble Space Telescope have captured the most comprehensive picture ever assembled of the evolving Universe — and one of the most colourful. The study is called the Ultraviolet Coverage of the Hubble Ultra Deep Field (UVUDF) project.

I’m wondering whether anyone has attempted to compute the value of the whole Universe, in dollars.

This strikes me as a crazy idea—a kind of reductio ad absurdum of the economist’s worldview. But people have come pretty close, so I figure it’s just a matter of time. We might as well try it now.

Let me explain.

The price of the Earth

There’s a trend toward trying to estimate the value of ‘ecosystem services’, which means ‘the benefits of nature to households, communities, and economies’. There’s a practical reason to do this. Governments are starting to offer money to farmers and landowners in exchange for managing their land in a way that provides some sort of ecological service. So, they want to know how much these services are worth. You can read about this trend here:

• Wikipedia, Payment for ecosystem services.

It’s a booming field in economics. So, it’s perhaps inevitable that eventually someone would try to estimate the value of ecosystem services that the whole Earth provides to humanity each year:

• Robert Costanza et al, The value of the world’s ecosystem services and natural capital, Nature 387 (1997), 253–260.

They came up with an estimate of $33 trillion per year, which was almost twice the global GDP at the time. More precisely:

Abstract. The services of ecological systems and the natural capital stocks that produce them are critical to the functioning of the Earth’s life-support system. They contribute to human welfare, both directly and indirectly, and therefore represent part of the total economic value of the planet. We have estimated the current economic value of 17 ecosystem services for 16 biomes, based on published studies and a few original calculations. For the entire biosphere, the value (most of which is outside the market) is estimated to be in the range of US $16–54 trillion (1012) per year, with an average of US $33 trillion per year. Because of the nature of the uncertainties, this must be considered a minimum estimate. Global gross national product total is around US $18 trillion per year.

You can read the paper if you’re interested in the methodology.

In 2014, some of the authors of this paper redid the assessment—using a slightly modified methodology but with more detailed 2011 data—and increased their estimate to between $125–145 trillion a year:

• Robert Costanza, Changes in the global value of ecosystem services, Global Environmental Change 26 (2014), 152–158.

They also estimated a $4.3–20.2 trillion loss of ecosystem services due to land use change during the period from 1997 to 2011. While still difficult to define, this loss per year could be more meaningful than the total value of ecosystem services. Sometimes a change in some quantity can be measured even when the quantity itself cannot: a famous example is the electrostatic potential!

The price of humanity

Back in 1984, before he became the famous guru of string theory, the physicist Ed Witten did a rough calculation and got a surprising result:

• Edward Witten, Cosmic separation of phases, Phys. Rev. D 30 (1984), 272–285.

Protons and neutrons are made of up and down quarks held together by gluons. Strange quarks are more massive and thus only show up in more short-lived particles. However, at high pressures, when nuclear matter becomes a quark-gluon plasma, a mix of up, down and strange quarks could have less energy than just ups and downs!

The reason is the Pauli exclusion principle. You can only fit one up and one down in each energy level (or two, if you count their spin), so as you pack in more the energy has to increase. But adding strange quarks to the mix means you can pack 3 quarks into each energy level (or 6, counting spin). So, you can have more quarks at low energies. At high pressures, this effect will become more important than the fact that strange quarks have more mass.

For this reason, astronomers have become interested in the possibility of ‘strange stars’, more dense than ordinary neutron stars:

• Fridolin Weber, Strange quark matter and compact stars, Progress in Particle and Nuclear Physics 54 (2005), 193–288.

Unfortunately, nobody has seen evidence for them, as far as I can tell.

But the really weird part is that Witten’s calculations suggested that ‘strange matter’, containing a mix of up, down and strange quarks, could even be more stable than normal matter at ordinary temperatures and pressures! His calculation was very rough, so I wouldn’t take this too seriously. The fact that we don’t actually see strange matter is a very good sign that it’s not more stable than ordinary matter. In principle ordinary matter could be just ‘metastable’, waiting to turn into strange matter under the right conditions—sort of like how water turned into ice-9 in Kurt Vonnegut’s novel Cat’s Cradle. But it seems implausible.

Nonetheless, when the Relativistic Heavy Ion Collider or RHIC was getting ready to start colliding nuclei at high speeds at the Brookhaven National Laboratory, some people got worried that the resulting quark-gluon plasma could turn into strange matter—and then catalyze a reaction in which the whole Earth was quickly transformed into strange matter!

This is interesting example of a disaster that would have huge consequences, that is very improbable, but for which it’s hard to estimate the precise probability—or the precise cost.

So, a debate started!

Needless to say, not all the participants behaved rationally. Frank Close, professor of physics at the University of Oxford, said:

the chance of this happening is like you winning the major prize on the lottery 3 weeks in succession; the problem is that people believe it is possible to win the lottery 3 weeks in succession.

Eventually John Marburger, the director of the Brookhaven National Laboratory, commissioned a risk assessment by a committee of physicists before authorizing RHIC to begin operating:

• R.L. Jaffe, W. Busza, J.Sandweiss and F. Wilczek, Review of speculative “disaster scenarios” at RHIC, 1999.

In 2000, a lawyer and former physics lab technician named Walter L. Wagner tried to stop experiments at RHIC by filing federal lawsuits in San Francisco and New York. Both suits were dismissed. The experiment went ahead, nuclei of gold were collided to form a quark-gluon plasma with a temperature of 4 trillion kelvin, and we lucked out: nothing bad happened.

This is very interesting, but what matters to me now is this book:

• Richard A. Posner, Catastrophe: Risk and Response, Oxford U. Press, Oxford, 2004.

in which a distinguished US judge attempted to do a cost-benefit analysis of the Relativistic Heavy Ion Collider.

He estimated a $600 million cost for constructing the device and a $1.1 billion cost for operating it for ten years (discounted at a rate of 3% per year). He guessed at a potential total benefit of $2.1 billion—which he said was probably a huge overestimate. This gave a net benefit of $400 million.

Then he took into account the risk that the experiment would destroy the Earth! He very conservatively estimated the price of a human life at $50,000. He multiplied this by the number of people now living, and doubled the result to include the value of all people who might live in the future, getting $600 trillion.

This may seem odd, but discounting the value of future goods can make even an endless stream of future human lives have a finite total value. More annoying to me is that he only took humans into account: as far as I can tell, he did not assign any value to any other organisms on the Earth!

But let’s not make fun of Posner: he freely admitted that this result was very rough and perhaps meaningless! He was clearly just trying to start a discussion. His book tries to examine both sides of every issue.

Anyway: his estimate of the cost of human extinction was $600 trillion. He then multiplied this by the probability that RHIC could wipe out the human race. He estimated that probability at 1 in 10 million per year, or 1 in a million for a ten-year-long experiment. So, he got $600 million as the extra cost of RHIC due to the possibility that it could make the human race go extinct.

Taking the net benefit of $400 million and subtracting this $600 million cost of our possible extinction, he got a negative number. So, he argued, we should not turn on RHIC.

Clearly there are lots of problems with this idea. I don’t believe the entire human race has a well-defined monetary value. I’m inclined to believe that monetary value only makes sense for things that you can buy and sell. But it’s not so easy to figure out the ‘correct’ way to make decisions that involve small probabilities of huge disasters.

The price of the Universe

Suppose, just for fun, that we accept Posner’s $600 trillion estimate for the value of the Earth. What then is the value of the Universe?

I think it’s a stupid question, but I feel sure someone is going to answer it someday, so it might as well be me. Maybe someone has already done it: if so, let me know. But let me give it a try.

I’ll be very relaxed about this, so it won’t take long.

We could try to calculate the value of the Universe by estimating the number of planets with intelligent life and multiplying that by $600 trillion. It’s very hard to guess the number of such planets per cubic megaparsec. But since the Universe seems to extend indefinitely, the result is infinite.

That’s my best estimate: infinity!

But that’s not very satisfying. What if we limit ourselves to the observable Universe?

No matter what I say, I’ll get in trouble, but let me estimate that there’s one intelligent civilization per galaxy.

A conservative estimate is that there are 100 billion galaxies in the observable universe. There might be twice as many, but perhaps a lot of them are small or less likely to support life for various other reasons.

So, I get $600 trillion times 100 billion, or

$60,000,000,000,000,000,000,000,000

as my estimate of the value of the observable Universe. That’s $6 × 1025, or $60 septillion.

The price of everything

The title of the article is taken from a line in Oscar Wilde’s play Lady Windermere’s Fan:

Cecil Graham: What is a cynic?

Lord Darlington: A man who knows the price of everything, and the value of nothing.