Works in Progress Podcast

Hey, welcome to the Works in Progress
podcast. We're here with Stian Westlake,

author of Capitalism Without
Capital, and Restarting the Future.

He's chair of the ESRC, the Economic
and Social Research Council,

Stian,

explain what intangible capital is and
what we should think differently about

the economy if we believe
that it's important.

The story about the intangible economy
or intangible capital is that capital,

the stuff that we invest in businesses,

governments spend money on something and
it delivers a return over a period of

time once upon a time.

Most capital was physical capital
that you could touch or feel machines,

vehicles, buildings. And over the last 40,

50 years that has been gradually changing
so that more and more of the capital

that we invest in is stuff that
you can't feel or touch. It's R&D,

it's software, it's data, it's
organisational development,

things like supply chains. It's even
things like brands and artistic originals.

So the Harry Potter universe is a great
example of a valuable intangible asset

created in the UK that's
pretty incontrovertible

from the data.

There's been now decades of measuring
this and showing how basically the

intangible capital line in all rich
countries has been going up for a really

long time. And the tangible capital line
as a percentage of GDP have been going

slightly down. So that's the
kind of core factual observation.

The claim that I would make and that
others who work in this area would make is

that that changes in some ways how the
economy works because intangible capital

is kind of different from tangible
capital in a few ways. Firstly,

it's scalable.

So something like a software
application or a dataset can be

used across an arbitrary large
business in a way that your machines,

you produce a certain number of goods,
you need a new machine to produce more.

And as you can imagine,
that leads to huge benefits.

You're going to get larger businesses,

there's going to be a natural
tendency for businesses to be large.

So people get very worried
about some large businesses,

and this is kind of an
argument, say, well,

to some extent you should expect this
in an intangible dominated economy. The

second thing is that these intangible
assets tend to have spillovers.

So if you invest a business invests in
some R&D or the design of a new product,

it's very hard for them to keep all the
benefits of that product to themselves

or that development, that idea,

it's easy to copy and that leads
you to the kind of classic can arrow

description of why you need to publicly
subsidise things like R&D so that

basically you get a role,

you get a situation where the type of
capital that you need for the economy to

grow will be under provided if you
just leave it to firms to provide it.

So there's a benefit to
public co-investment. Also,

the idea that these assets
are particularly valuable
when you combine them

together, they have synergies.

And one of the things that
that means is that what

economists call agglomeration,
the benefits of cities,
the benefits of thriving,

dynamic cities, clusters,

places where people can come together
and bring their ideas together,

or they could be online places,

but so far this stuff seems
to work better. Face-to-face
agglomeration is going

to become more and more important.

And then the final kind of way that
these intangible assets differ is there

often a sunk cost. So if a
business owns some brands,

if it owns some valuable software,

it's often very hard for that to be
taken for creditors to take a charge on

that, for that to be passed
onto another business.

And that creates a really big problem
from a financial point of view because

most the modal business finance
in the UK or in other rich

countries is debt
finance. It's a bank loan,

and what banks really like is
collateral. Once upon a time,

the classic business had a bunch of
tangible assets that you could take as

collateral. And so the banking
system worked quite well.

Debt is a really simple form of
finance. It's really easy to understand.

Increasingly businesses have
less and less useful collateral,

and that creates a challenge if you've
got a debt-based finance. And it's why,

for example,

we've seen the kind of rise and rise
of venture capital over the last 40,

50 years because venture capital is,
it's obviously equity based finance.

It's the ideal type of finance
for an extremely fast growing,

intangible based company.

It's really a kind of sign of
a harbinger of the intangible

economy. So I haven't got around to your
question about what would you change.

Actually, let me,

because you are hitting
on my pet theory of the

housing and cities problem that the
world has, Right? Because the big,

big, big counter argument to the claim
that I make and that Ben makes that

housing shortages are the reason that
most western economies are not growing

very quickly or not growing as quickly
as they could, or not very quickly.

I don't really need to hedge that,

is that we're not building enough houses
specifically in prosperous cities.

And the counterargument is, well,

this all seemed to set in around 2008
when the financial crisis happened.

That's a weird coincidence that like, oh,

we just started building too few houses
when there was this huge financial

crisis and just never recovered from
that. Just at the time that you're saying,

we stopped building enough houses,

and I think that what you're talking
about might help to explain that.

It could be that we're just wrong. I'm
not discounting that. But if we're right,

because there are loads of other
arguments to say that we're right Then one

reason might be that the rise of the
intangible economy coincides with not 2008

specifically, but the two thousands

The 2000 and tens and the
2020s. Because it's not just,

you were saying that synergies
are the reason that cities matter,

but what you're describing
the scalability point,

another way of saying that is you don't
need that much land and physical capital

for a given size.

So usually if you're building a
car company or if you're building a

manufacturing company,

land and space are really valuable
and you need to spread out across

some area of land.

You can't have a successful Volkswagen
unit in the centre of London or in the

centre of Berlin. You need to
build it outside somewhere.

An economy built on tangible capital
or manufacturing needs to be spread

out. And you can see just observationally
countries in Europe that have more

manufacturing intensive economies
like Germany are more spread out.

They're not centred on a single city.

Absolutely. You've got these huge
companies in these pretty small towns.

The point about spillovers,
now, spillovers don't have
to be local spillovers,

but they often are local
spillovers. If you think about,

and maybe you can talk
about how spillovers happen,

what actually is going on
when there's a spillover,

and obviously it can just be,

I'm looking at the app that somebody
has made in Shanghai and copying It,

but
Often a spillover can be, well,

we've poached person who works for
this company. Right, completely.

So you want big pools of labour so that
people can easily change jobs. Exactly.

And often the classic spillover
is basically a kind of, I dunno,

low key theft or not. It's uncompensated.
That's too strong a word, sorry. But.

I'm happy with theft. I'm an IP, I've
become a total born again IP maximalist,

so I'm happy with that.

So the classic spillover is kind of
an uncompensated one, but as you say,

these things can often be, they
can be perfectly well compensated.

You can work with someone,
you can say, oh, well,

we will pay you a bit for that.
You might not be happy with it.

You might hire someone's employee.

These things can happen
in a whole number of ways.

I guess what we know is that in theory,

they can happen across an unlimited
amount of distance because we have

telecommunications and we have zoom,
and we have all these wonderful things,

but I guess intuitively,

most of us have a feeling that they don't
work as well from that point of view,

and that there is something
about face-to-face communication.

There's something about serendipitous
interaction that at least for the time

being still seems to make
those transfers of information

or trusted transfers of
information easier to do.

Yeah, I mean,

I have all my best ideas when I meet
somebody for a coffee or meet somebody in

the pub and I'm chatting with them,

they work in a different sector and
they say something and I'm like, oh,

what about dah, dah, dah, dah.
And then it's like, oh, right.

That's really interesting. I'd
never thought about that, but oh,

it turns out this thing that I
know that I thought was irrelevant,

redundant knowledge applied to thing,

the problem that you've got with
knowledge I didn't have before,

maybe there's a solution there
that's effectively a benign,

that's a benign spill over. Totally.

Yeah, exactly.

Yeah,

and the reason this is so cool to me or
interesting to me is that if this model

is right,

then this is the key that
explains the timing of what I

call the housing theory
of everything. Well,

the housing shortages being really
important and the 2008 timing

is actually a coincidence. And
actually that's like, okay,

it's a big coincidence and
I'm not discounting it and
I'm not trying to dismiss

this point because an important point,

and there are actually other factors
that do relate to that that we won't go

into here,

but it's possible that the
rise of the intangible economy,

or sounds to me like the rise of
the intangible economy is the demand

side part of the puzzle where we always
talk about the supply side part of the

puzzle. There's not enough supply.

What we don't talk about is why there
is so much more demand to live in London

now than there was to live in
London 50 years ago or 40 years ago.

Yeah, no, you're completely right.
And I mean there's an interesting,

if we can get historical for a second,

if you look at some of the earliest
anti city critiques, I mean,

what to me are the early,
maybe I'm out of date here,

but think it's people like Thomas
Jefferson who were very down on cities.

There's a kind of interesting story of
the evolution of the technologies of

production changing
people's views of cities.

So Thomas Jefferson's story about cities
were the countryside was where virtuous

work was done, it was
where agriculture was done,

and that was what really created
wealth he was thinking about.

He had this model based on,

I guess ancient Rome where
agriculture created wealth,

which in ancient Rome probably
that was broadly true.

Most people basically have that
mind and that vision in their mind,

they just add raw materials.

They just add into it.

Most people basically think that.

But if you're in 1780 or whatever, and
when you look to cities, he was like,

well, what happens in cities? People
suck up to the king or whoever,

and the king gives them stuff. And it's
not stuff the king's created it's stuff.

The king has taken it from someone and
he gives it to these kind of terrible

mosquito curers who flock around.

So the model of the city in the kind
of pre-modern model of the city is

basically this extractive institution.

It exists to confiscate the
surplus and to give it to

people who practise stuff that's basically
destructive rent seeking activity.

It's like it's a parasite. It's like a.

They're like parasites.

It's like the days when people were
granted the monopoly on something by

Elizabeth the first just because they
were kind of a friend or whatever.

And so people like Thomas
Jefferson were like,

cities are basically bad and they're full
of disease and all this kind of thing.

And actually in a pre-modern world,
it's not entirely wrong. I mean,

cities did do more than that and
he was probably wrong in 1780,

but it wouldn't have been hugely out for
really a mediaeval city or an abalone

city.

And I guess what that line of
thinking probably leads into

Ebenezer Howard and his sort
of scepticism of cities,

all the kind of William Morris type
philosophy that probably informed the UK's

restricted planning laws and perhaps.

Henry George who attended land value
taxes to basically destroy cities.

Yeah, there's a sort of sense in which

there is method to the madness in that
if your model of what's going on in the

economy is this stuff doesn't,
cities doesn't matter very much.

And to come back to what
you were saying before,

you were kind of painting this picture
of a country like Germany that has these

very,

very productive businesses in kind of
the middle of nowhere in Wolfsburg or

wherever the biggest businesses
aren't in Berlin. They're in kind of.

Apologies to our listeners
in Wolfsburg, but.

Sorry, yeah, lovely place, very productive
place as well, but not a big city.

If your model of the economy is that
it's not as extreme as Thomas Jefferson's

economy with the courtier,

but your production is going on in
places where you can build big factories,

where workers can live in sanitary
conditions like the kind of

model towns, salt air and
places like this in the uk.

And again, there's a
kind of logic to that.

And what we're basically saying
is that logic of production,

the underlying dynamic has changed.

And because that's unfortunately we
are reliant on a set of laws certainly

in the uk, the US and in probably a lot
of other AMO Saxon countries at least,

that were based on a kind of an old
fashioned model of how production works.

So going to, what would you think
differently about the economy?

I have a suggestion which is
lots of people think that tech

companies, very large tech,

what most people think of as tech
monopolies like your Googles or your

Facebooks, your Metas,

that one of the big advantages they
have is that switching costs are high.

So you invest in Google and is
really difficult to switch away,

so you're stuck with them. New entrants
don't have a way of getting in,

and basically the market is
monopolised by virtue of that.

Now I think that's probably
the case to some extent.

I don't think those companies are
actually monopolies in an important sense,

but we don't need to get into that.

But what I think people don't
really understand is that
in a world where we have

infinitely scalable software where in
principle every single person on the

planet could use Instagram
or could use from a

software point of view,

they could all use Google Docs.
Let's say switching costs being zero.

If we imagined a world where it was
completely free to switch would lead to if

everybody had the same tastes,

at least would lead to everybody using
the same piece of software, everybody,

and they might switch overnight.
If a better Google Docs came along,

they might then all switch.

They would all switch at the same time
to this sort of superior like Ulta Vista

Docs or whatever the new thing was.

But people conclude from the size of
these platforms that they are monopolistic

and that they are essentially that
they have extreme market dominance.

When we would expect to see in
a much more competitive market,

we would expect to see much larger
and much more dominant platforms.

So to be clear,

I'm not saying that we can conclude
from the fact that they're big,

that the market is competitive,

that that's a different
question for different data.

There are other things we can look at,

but I think because people don't think
about scale and they don't think about

what it looks like when it's free
essentially to provide your products to

another customer,

they don't think about what that implies
for the kind of natural or efficient

size of companies in that marketplace.

Yeah, I think that's really right.

So I think you are absolutely right
that the efficient size of a company and

when your capital is scalable
is going to be really large.

I think the other thing is that although
scalability allows large companies,

it also allows new companies attackers
to very quickly take over that market.

So I guess what you'd see,

I mean the classic paradigm of competitive
market in the kind of old economy

is you've got a certain
number of competitors,

you've got at least eight competitors
or at least four competitors or that's

what it looks like. I think in a kind
of more intangible dominated sector,

what you'd actually see as punctuated
equilibrium where one company has an

absolutely vast market share for some
number of years and then it collapses

like a pile of sand and then
Google takes over from Yahoo

and whatever takes over from open.

AI takes over from Google,
open over from Google.

Now I realise that if you are
a kind of hardcore person who

thinks competition's a big problem,

if you're a kind of neo brandand
economist looking at this, you'll be like,

well,

how can I trust you that the
current monopolists are going to

be replaced by the next generation?

And I admit that's the challenge you
can't prove. You can't predict the future.

But it does feel that that to some extent
does describe what's happened in quite

a lot of tech sectors up until now.
And if it suddenly stopped happening,

if there was total lock in
on the existing platforms,

then I guess then I'd start to doubt.

But the punctuated equilibrium does
seem to describe what's going on. Yeah.

I think the key point to me is
inferring from the size of a

platform that it is monopolistic is
basically getting it the wrong way around.

Exactly. It just doesn't
give you a strong signal.

It could be big because it frustrates
competition or because there are features

of the market that make
it difficult to compete.

So basically active anti-competitive
behaviour or just passive

market features or it could be big
because that's what consumers choose.

And in a world where you can provide
your product to anybody in the planet,

consumers just get what they want and
they all herd around the thing that they

want most. Right? Yeah. So do
you think there's a tension,

so Ben and I both wrote this essay
along with our colleague Samuel called

Foundations,

and I think you would hopefully share
a lot of our diagnosis around big.

I'm a big fan of Foundations.

Housing and infrastructure because
we're talking about cities,

we're talking about people and the
ability to move and work with each other.

Sure, place matters on
the intensive margin,

but less so on the extensive margin is
the kind of intangible capital world.

But energy is the other thing that we
point to and where we say that energy is

incredibly important that you cannot
understand British or European sclerosis

without relative to the US without
looking at the rise in energy prices

in Britain and Europe
relative to the United States.

But energy is much less important
to the intangible economy.

And I gather maybe there are
exceptions, maybe AI is an exception,

but for the most part,
energy is not that important.

Do you think that we're basically
wrong or do you think that there's a,

have we over-indexed on basically
a fundamentally kind of dying

part of the economy or is it that
it's important but it's just residual?

Yeah, so it's a really interesting
question. I genuinely dunno the answer.

I think you're right to highlight AI as
a possible exception because it might

well be that the nature of AI is that
there is a huge benefit to actually being

able to domestically run
huge AI based data centres.

And if that's the case,

we've identified a kind of surprising
type of intangible capital that relies,

that requires lots of energy. So let's
park that and just say setting AI aside,

what do we think more broadly?

I guess I definitely agree with you
that high energy costs are a problem.

High energy or costs seem to be a
problem for manufacturing sectors.

They're certainly a problem for what
sometimes get called foundational

manufacturing sectors like
basic materials and so forth.

I guess the interesting
question is do you actually,

if you didn't have that,

let's suppose you had to have an economy
that was largely based on services that

weren't particularly energy
intensive because your electricity in

your country was super
expensive, so you're buying
that stuff in from elsewhere.

Could that work? I guess
my view is that could work.

It feels to me that you can have a
kind of manufacturing manufacture goods

are tradable. You could basically
trade in low value manufactured goods,

produce high value manufactured
goods where energy are

a lower proportion of the
costs and have that work. Well,

I guess where I agree with you regardless
of that is that that probably isn't

where the UK is starting from now,

the UK for all that we meme ourselves into

thinking this isn't true,

UK actually does have a pretty
sizable manufacturing sector,

almost the same size as France.
We're not as big as Germany,

but Germany is really, really weird.

Germany has a huge manufacturing sector
relative to other rich countries.

So manufacturing does matter in the uk and

certainly for a lot of manufacturing it
seems that energy costs are a problem.

I guess the other question that is
I don't feel I have an answer to,

some people have got very
strong views on it, is

there some kind of synergy between
these so-called foundational,

extremely energy intensive bits of
the manufacturing economy and very

high value ones where energy is
a smaller part of the market,

which is certainly something people hear.

I mean the whole concept
of foundational industries,

that's what it's meant to imply.

It's meant to imply you need
that if you want the other areas.

And it seems like perhaps it's plausible,

perhaps there's some transferable skills
between the two and therefore that

there are ironically some intangibles
that are created by having a huge glass

making industry or something
that then flow into more advanced

manufacturing.

But I guess what I'm saying is in theory
if the UK was a totally post-industrial

economy, then I might say energy
costs might not matter very much.

You could just do without them. The
fact is that's not where the UK is.

So energy costs probably do matter.

What about manufacturing
innovative manufacturing companies,

and I actually don't know about this,

how important energy costs
are to startup innovators

that do physical stuff.

There is obviously a tonne of innovation
that could happen in the physical world

that is basically the intersection of
the intangible economy and the tangible

economy.

There's a tonne of ideas that require
the application of the idea to the

physical world,

and I don't actually have a good sense
of how important energy costs are as a

constraint on what they.

Can do. Neither do. I
mean if I had to guess,

I would think that if there is a
transmission mechanism from high energy

costs to underperforming
advanced manufacturing,

it's not so much that the energy
costs directly affect them,

but it's that they undermine, sorry,
I'm going to get a bit heterodox here,

but they undermine the kind of
industrial commons that they depend on.

So certainly what are the industrial
commons? So I mean this is again,

what does that mean? This is a bit of
an intangible idea, but the idea that,

well,

to take an example of where there is
something that's arguably in industrial

commons, if you look at some of the
big manufacturing clusters in China,

the story that I hear told about
them is there's just a huge amount of

general manufacturing skill that goes
around in the same way that in the UK

there's a lot of skill in the creative
industries that is totally tacit,

that is just generated by lots of people
working on things in an area. It's the

kind of classic Alfred Marshall clusters
theory from the early 20th century.

If that's true,

it basically suggests that having
a lot of manufacturing output is

synergistic with the next incremental
bit of manufacturing output because the

skills are there.

Certainly if you talk to the people
at the Institute for Manufacturing at

Cambridge, they're very big on this.

They kind of will give you
lots of qualitative evidence.

I've not seen much
quantitative evidence and

I accept that some people will be
sceptical of this because they'll say,

surely this is just a kind
of manufacturing just so
story. On the other hand,

we know clusters exist,

we know that the kind of knowledge
does get transmitted so that you'd

effectively get this kind of
transmission from high energy costs,

smaller manufacturing sector driving it,

driving out the lower value added
stuff and that effectively because

there are synergies between the two,

meaning that it's harder to get the
skills to do it's speculative. Yeah.

I have a couple of questions on
the bit jumping into a new area,

but it draws on everything
we've been talking about.

So if you ran a developing country,

would your view be that if
you ran a developing country
and you're also still in

Westlake,

so you have your background and the reason
they picked you to around the country

is because of the knowledge,
the things you know about,

would you advise them to do try
and jump right to high tech stuff?

Would you build an ITRI if
you were Taiwan in the 1950s,

would you be trying to jump,
right, if you're India right now,

do you want to build a massive space
organisation or are you trying to do the

most high tech chip manufacturing or
would your view be like the Chinese

clusters you were talking about?

Which of you be like get the
basic stuff and then steadily,

incrementally get better at technology?

That's such an interesting question.

So I've definitely not putting myself
forward for this role, I dunno,

but I guess on the one
hand there is a real,

if you can make the leap then you avoid
a lot of potential development traps.

We know these middle income traps that
countries can get caught in if they try

and take the standard path,

not least because China will outproduce
them in various areas if they

try and go from agriculture to
manufacturing into services.

I know I've often heard people involved
in economic development in Ireland tell

the story that Ireland went straight from
a pre manufacturing or pre-industrial

to a post-industrial state.

And it looks to me like the work that
they did in terms of developing call

centres, attracting
foreign direct investment,

acting as a kind of corporate or a
corporate local headquarters base

that seemed to work. I mean it seems
to have made Island very prosperous.

So I'm interested in that, but what
I'm really thinking about is more

not the economic stages
of tertiary employment,

but the level of tech.

Oh, I see what you mean.

For example, Britain in the 1950s, 1960s,

1970s went very heavy into let's
make the best train in the world,

let's make the best nuclear
power station in the world,

let's make the best plane in
the world. And to some extent,

to lesser or greater degrees,

they somewhat succeeded in actually
generating the advanced passenger train,

but they're not actually doing it.

And then building the advanced gas
reactors by modern standards probably look

quite good, but certainly by their
standards looked really bad, Concord,

et cetera, should they be
trying things like that.

Yeah, that's such an interesting question.

I mean I think at the core of that is
the idea that you can be too innovative,

you can overinvest in R&D relative to
other things that you might auto invest in

and yeah, I mean my gut feeling,

especially when you frame
it that way is you probably,

that's probably a mistake.

Now the question comes what's the
right balance to strike between

old stuff and new stuff? But I mean

being at the technological frontier feels
almost like an unnecessary place for a

developing country to be
because you don't need to be,

you can just copy things that work and
ideally you can kind of do it in a way

that avoids some of the path dependent
mistakes that other countries might have

made.

I want to talk about scaling where it
seems to fail in the intangible economy,

which is food and restaurants.

Yes.

Restaurants try to become chains. They
almost always fail in my experience,

in my observed experience,
either they fail,

they almost always fail economically,
They basically always fail.

There's one exception that I'm
aware of which is Honest Burger,

they basically always fail in terms of
the quality of what they're doing when

what they're doing is entirely intangible.

It is essentially recipes
and a business model.

There's a certain tangibility which is
like you need a restaurant and you need a

chef and you need and so on.

But the thing you are transferring
between essentially homogenous kitchens

is ideas.

And why is it that scaling I think
completely fails when restaurants

try to chain almost always fails
if it seems to work in other areas.

What's the thing that makes
restaurants or food different?

It's really interesting. I wonder if
there's kind of two things going on here.

So I think there is something which
is pretty much what you described,

that it is just hard to
transmit the knowledge of

how to cook something in a particular
way between different artisanal

people cooking in different
restaurants. It's difficult to codify,

it's difficult to make
that very, very precise.

And I mean that seems to be empirically
true that when these change expand very

fast,

they're perhaps dependent on extremely
high skilled motivated people in their

kind of original location. And that just
recruiting at that scale is hard to do.

I mean if you are McDonald's and you've
got an extremely well specified process

and significant physical capital
to kind of automate the process,

you can get away with it. Certainly
for me, a McDonald's burger in, yeah.

McDonald's is a very genuine, very
scalable, that works really well. One of,

I mean clearly the most successful scaled
restaurant in the world, no question.

Exactly, and has incredibly consistent
quality. And that's part of the idea.

And I guess partly that is because a
lot of you've worked in a McDonald's I

haven't. But a lot of this is kind of
that it's dependent on physical capital.

There's a lot of capital in a McDonald's
kitchen that allows things to be

replicated because physical capital you
can mass produce in a way that you can't

mass produce cooks. So that probably

helps. Making the offer relatively
simple probably helps as well.

So I think there is just something that
if you scale a business based on hiring

more people and trying to get 'em
to replicate a process, it's hard.

So when I think about my early days
working in management consulting,

that was a service-based business.

That base in McKinsey was a service-based
business that basically replicated a

process flow,

a pretty standard flow of recruiting
people and of doing projects

across, I dunno how many countries,

dozens of countries. But the amount
of investment that went into building

the culture into ensuring the
right kind of hiring practises

was, I mean people sometimes
disparagingly call it cult-like,

but I don't doubt for a moment
that that level of culture

control and conscious generation of
culture was necessary to do that.

Now if you're Byron Berger, you're
not making those kinds of investments,

you're not sending your new Burger
Chef on a kind of intense offsite day

and selecting them individually
through five rounds of interviews.

It's just a different process.

So I think there is one thing that
just scaling at a lower end of offering

where you are reliant on kind of
artisanal processes is harder.

I was just wondering if anyone had
ever been to Cheesecake Factory,

because I gather they have a really
long menu and it's really consistent and

really good.

It's gone downhill unfortunately.

Oh damn. So they followed the
same rule. It was incredible.

Years ago, I wasn't a fan, but might
be, I think it was amazing 10 years ago,

but I think it's gone downhill.

I wanted to also add another
example, which is that coffee,

you might think that coffee,
so especially espresso,

the same core bit is going into all of.

Yeah.

The drinks. And yet in the article Nick
Whitaker wrote for us, our ex colleague,

he points out that they basically never
managed to scale either machines because

there are so many difficult moving parts
or there maybe they're getting to that

now or coffee shops,

even coffee shop chains don't generally
manage to scale that well because there

are certain things like
dialling in the buzz as he says.

One of the things that you just need to
have process knowledge is really hard to

get it without a) learning by doing and
b) apprenticing to someone who's really

good. And so it's really difficult to
scale high-end third wave coffee shops.

Example. That's a great example.
I guess the other dimension,

so to take a totally different
tack on your question,

you sort of started with the premise that
chain restaurants fail and empirically

they fail in the sense that they're very
popular and then they become bad and

then they close down. So that
is a certain sense of failure.

I guess there's an interesting question
of saying is that really failure,

and I guess what I mean by that is if
you think of the brand or the brand

and the menu and the offering of
a restaurant as basically a bit of

intangible capital,
it's the business idea.

What we know about a lot
of creative industries,

and I would consider restaurant
food to be affiliated to that,

is that tastes change to be really
kind of simplistic about it.

And in a way you could see that as being
capital that depreciates. So if you

come up with say, I dunno,
Byron Burger as a great example,

a particular set of offerings around
a kind of relatively high quality

burger in a sort of fast food setting,

it may just be that extending that brand
forever that the brand has a shelf life

in the same way that
if you buy a computer,

the computer you affirm buys a computer,

it'll depreciate that computer over a
period of time and that the end of life of

that computer makes sense. So if
you look at the, what do we call it?

Like the fast casual food
sector, fast casual, yeah.

If you talk about the fast casual food
sector as basically a set of people who

will,

they'll create brands or rather they will
go and find individual restaurants and

say, this has the potential to be
a brand. They'll take that brand,

they'll scale it to the
best of their ability,

but given with the limits that you
can't invest unlimitedly in the human

capital to get the baristas making the
perfect coffee or cooking the perfect

burger, but you do the best you can.

So it scales acceptably
for a period of time,

but that brand will only
have maybe a seven year life.

And I guess when we look at
firms that don't work like that,

you look at McDonald's,
you look at Pizza Express,

that maybe they're weird exceptions
that we shouldn't be judging the things

by maybe actually a healthy industry
looks like Byron Burger is big

for five years and I don't know,

Wahaca is big for five years
and then they go to seed.

Well do the investors who do
that make money on the long run?

I mean if they do then
that sounds correct.

If they end up becoming poorer because
of what they've done then that sounds

like that isn't the case. It's.

A good question. I mean I
see you'd hope they are.

I mean you need to get Luke
Johnson on and ask him,

but I assume these people do make money
out of it because they keep on coming

back. I think it's probably different if
you're looking at the high end one-off

restaurant business,

I get the feeling that a lot of people
open a restaurant and it's kind of a

consumption good. That's
a sort of different story.

But I'm assuming that if you take
a fast casual chain that operates

for a decent number of years,

quite a lot of people have made
a lot of money out of that.

Here's a question I have for you.

So a thing I think about a
lot is how within government

when we try and solve a
new problem, you take the

existing organisational structures
and existing teams say, okay,

let's take these guys, let's
go and solve the new problem.

So anything new that happens,
if it's the home offices area,

the home office solves it In business,

generally what happens is IBM
tries to solve the problem of

personal computers in the two thousands
and then someone else starts a company

which, and in fact that
solves the problem.

And so we all just shift across. Now
I am wondering is intangible capital,

does intangible capital mean
that we do more of that,

like extremely rapid shifting from That's
interesting from one thing to another

and has is the world of intangible
capital made us therefore less

our government structures becoming more
sclerotic because of their inability to

create new organisations?

Because you are saying that intangible
capital is a recipe for doing something,

we always have to use the same recipe
and try and update it a little bit rather

than having completely new recipes.

Is this a bigger problem now
than it was 50 years ago?

I dunno if this is exactly
the same as you're asking,

but I do think that the
rise of the importance of
intangible capital puts a real

burden on government to generate new
institutions, new effective institutions.

So case in point, when we're looking
at intellectual property rights,

which you briefly mentioned earlier,

it intellectual property rights
are really tricky to work

out.

No one has a particularly good intuitive
moral feel about who should own stuff,

that you can have people making
this very passionate case that

artists should have very strong rights
over the things they create. Equally,

you can have people saying
copyright is really a moral,

and those people will be as
morally impassioned as the artists.

Our moral intuitions are quite all
over the place on intellectual property

rights.

But we also know that intangible property
rights get more and more important and

intangible economy, there are more
intangible assets you work out,

you need to work out who owns them and

both the need to own those
things because if there was no

intellectual property rights at all,

then you would imagine that people
would produce fewer of the relevant

intangible assets. But at the same
time, the ability to combine them,

which kind of effectively relies
on slightly weaker assets.

Because if you sort of say classic case
in point that we're seeing in the debate

about copyright and AI at the moment,

I think if you allowed
the creative industries to
entirely set the terms of the

debate,

you'd basically have AI models wouldn't
be allowed to train on any creative data

or only at an absolutely exorbitant price.

It was unilaterally decided by creatives
who weren't necessarily well informed

about what the market would bear.

So you kind of want to combine things
and you basically need institutions to

govern that. In a sense, the intellectual
property rights is one institution,

copyright exchanges are
another set of institutions,

but those institutions don't exist at
the moment. And you kind of say, well,

okay, what's government's track
record at creating new institutions?

It's not great. I mean it was
probably pretty good in the 1850s.

The 1850s governments created lots of
institutions and civil society created

lots of institutions. We probably
are less good at doing that now.

So I think that's a real
challenge for government.

Okay, Stian, so you run the ESRC.
We now have this organisation, ARIA,

which has complete freedom to take bets
on all the kinds of things that are

really going to change the world given
that we have this inspired by ARPA and

DARPA that did such amazing things in the
us why would we keep your organisation

going? We just roll it into ARIA.

It's the justify your existence question.

I think when it comes to research funding,

one thing that we know
we need is a portfolio,

a mixed portfolio of different
ways of doing things.

So ARIA and things like ARPA
that ARIA is based on is hugely

important.

I think doing really radical blue
sky research and innovation is

really important. It's a really important
part of the mix. But to get that,

to make that happen,

you also need a bunch of other things
that's part of almost like a value chain.

You need someone to fund your
PhD students in the first place.

You need to fund people to
get their training, however
they're going to do that,

you need infrastructure.

So we spend probably about coming up to
a third of our budget on providing data

infrastructures, which basically
allow people to do social science.

And that's the kind of thing ARIA doesn't
do that they rely on people like us

to do it. And then

the thing that I find kind of interesting
is as well as breakthrough research,

you do also need incremental research
people to work on smaller projects,

more longer term projects that
are part of research's curiosity.

And I think the system before was
lacking something when we didn't have

ARIA,

but I think you don't want just ARIA in
the same way that you don't want just

funding PhDs or just funding big
grants for mature researchers.

Can you tell me more about data
infrastructure? What is that?

So let me give you an example.

For quite a while there's been a talking
point about certain university degrees

not being worth doing and people will
say, look, we've looked at the data.

If you study these particular subjects,

you will have a low income
and it's suggesting that
these things aren't leading

to graduate jobs.

Where all of that comes from is merging
together two government data sets,

what we call two administrative data sets,

data sets created when the government
does its business. One is tax data,

which gives you really accurate
records of what people are earning.

And the other is the life course
data on people's education.

So where they went to school,
what grades they got at school,

what they studied at university.

Those two data sets sit in entirely
different places in government and no one

combines them.

One of the things that we
fund is a project called
Administrative Data Research

uk,

which basically goes works with government
and merges those data sets so that

people can do research on them. Like the
research that was done to work out that

some degrees you earn a lot of money if
you do them and some degrees you don't.

And that's a good example of the
kind of research that we fund.

We are now looking at data
infrastructures, looking at new data.

Data's created by social media
data created by smart cards.

And I guess what's interesting about this,

if you think about the
incentives on researchers,

researchers got a huge incentive to get
their own private data store and then

max out the papers they produce from it
churn out the papers and actually they

don't have a huge amount of incentive to
let other people see that data. For us,

this is infrastructure for us,

there's a huge benefit to saying let's
prepare the data and then let's make that

as widely known as possible so people
can do as much research as they can.

So I'm curious about this merging data
sets thing because it's a big bug bear I

have for various reasons.
Is this a cumulative thing?

Is it like electrifying different train
networks you go through and you've

joined that dataset?

Now we can do loads of work with that
joined dataset or is it more like a

one-off project thing where we have a
bunch of insights and then next year it's

not joined?

So it's more like the first.
So once you join them,

you can use them again and again because
actually most of the work in joining

these data sets, it's not really
technical work. It's not computer science,

it's not software, it's kind of
emotional labour as they'd say.

It's going to the people who are
responsible for these data sets in the

government and convincing them that
they are not going to get in trouble,

that the politician who is their
boss is not going to get in trouble.

If you can look at one data set
about crime alongside another data

set about health outcomes.

And it's not that people who
work for the government are,

it's not that they want
keep these data sets secret,

it's just that they're risk
averse what will happen.

So once you've done that work,

then you can make the data
sets more widely available.

So I need to hear more about
which there are so many,

I'd love to join up and what's
going to happen next on these.

Because for example,

maybe I shouldn't say who a person
related to me very closely as a doctor and

she has had many, many,

many different troubles in
her job from the alleged,

the belief that many people have that
you aren't able to join up various

different data sets. You're allowed
to view one, type it into another,

and that's fine because the doctor would
be able to see both those things and

the doctor will be able
to insert those data sets.

But it's perceived that there are various
issues with joining them up and having

all that information to hand.

And so doctors waste hours of their
time creating new lists every day,

et cetera, et cetera.

Now sometimes that's because they haven't
invested properly in it or whatever

reason, but I think there
are a lot of cases where

the data isn't joined up.
And then related to that,

there are also things where I feel like
we don't even have basic correlations

where we could easily at least start
the research off by saying, okay,

well look, there's this big question now
about whether illness burden is driving

disability rates, claimant rates
in use in universal credit,

the UK's benefit system up.

And there's a huge question of is it
that the system is more exploitable after

the existence of TikTok or is it the
system is more exploitable because UC is

worse than the previous system
which have been heavily patched?

Or is it that we've got much
higher illness burden since COVID?

I feel like could you
answer those things for.

Me? There is so much that we can
do, so I can't answer them now.

We're doing actually department for
work and pensions who handle the UK's

claimant data.

We've now just started to do a load of
work with them merging their data sets.

So I hope some of these questions are
going to be more answerable in future.

I mean it's interesting just to come
back to this kind of original question

about, well,

what's the point of why do you have
these government organisations funding

research?

A while ago I came across an interesting
paper that's about a decade old by

Tyler Cohen and Alex
Tabarrok, the economists,

and it was basically about the
US' economics funding public

economics funder.

So it was what of the National Science
Foundation Fund when it comes to

economics.

And I'd probably been doing the job for
about a year when I picked this up and I

thought, oh goodness me,

this is basically going to tell me that
everything I've been doing is wrong and

I need to totally rethink.
And I think Tyler's great.

So I was thinking I'm going to
feel very conflicted at this point.

It's really interesting what he said he
thought the US public science funders

should come fund when
it comes to economics.

He basically said data infrastructures,

he said translational work.

So there are lots of insights that come
from economics about how you should run.

For example, the housing
and the planning system,

something that I know you talk about,
a lot of that is locked away in papers.

Sometimes they're in journals
that policy makers can't read,

but in any case they're, they're
designed to be read by scholars,

not by public policy makers. And
he was sort of saying, well look,

you should fund translational work
to make these things accessible.

And then he also said you
should fund replications.

So fixing the reproducibility
issue, and he was saying the things,

these are underfunded things that
public funders should focus on because

actually academics will do
the other work themselves.

And actually when I look at where
we now spend most of our budget,

we spend, as I say, almost a
third on data infrastructures.

We spend about 10% on what
we call translational work.

So we fund something called
the Economics Observatory,

which is trying to translate some of these
insights into stuff that's useful for

policy makers. The one thing we
don't do a lot of is replication.

That's a really interesting question
about how much more there is scope to do

when it comes to trying to replicate
some of these social science studies.

Go ahead. To bolt onto that, it
would be great to have a couple of,

there are guys, I think it was bigger
in the 2010s and in the two thousands,

but there were a lot of people on the
internet who got their reputation from

basically fisk things.

And I feel like sometimes there you can
get a career out of that or you can get

lots of prestige out of
it. So we get enough of it,

but probably in general we do too little
of it because if you're to be that

person,

you have to have a very specific mindset
to be willing to make everyone angry

with you and so on. And there are
some people who really like that,

but maybe not enough of them.

There are so many incentives to at knuckle
under and be part of the gang and so

on. So maybe funding like a bunch of SCAs
who are constantly checking everything

would be.

You should get Michael
Wiebe. Do you know him?

Yeah.

He just does these replications
that are absolutely,

I mean they're brutal because he does
replications of studies that I like as

well.

And they often turn out to be not as good
at either just bogus or not as good as

you had hoped. And you have
to update based on that,

but it's a lot of work.

And how do you overcome the fact that
there's no prestige in this and you're

actually,

it seems like academics look down their
noses on people who do replications.

They say that they like replications,
but if you actually do replications,

it seems like not very good for your
career and you have to be a true believer

like Michael to actually
be willing to do it.

I mean there's definitely some things
that are favoured in academia and some

things are disfavored. So translational
work generally disfavored replications,

there are some people who are
into replications, but as you say,

it's not the classic way to get your
top economics journal publication and

actually data infrastructures as well.

This is part of the reason why Tyler
thinks it's worth publicly funding it

because it's not the kind of thing
academics are intrinsically motivated or

motivated by prestige intrinsic
to the economics discipline to do

so. Again, this comes back
to this idea of a portfolio.

You wouldn't want everyone doing
replications because then there'd be no

research to replicate,

but you probably would want a bit
of your portfolio looking at that.

How do you allocate across for different
envelopes when it comes to PhDs?

How do you decide how much
money should be going into PhDs?

And then also how do you decide
how much should go to economics,

how much should go to other social
sciences, political science,

whichever other disciplines
that you end up funding.

So it's a really good question because
I'm kind of trying to reflect on this at

the moment. I can tell you how
we do it now. So at the moment,

there's basically two ways that the
government funds PhDs in the uk.

Most social science PhDs aren't funded
by the government at all and aren't

funded by us.

They're people doing them pretty
much they're self paying for their

PhDs or in a few cases they're
funded by some other funders.

But the PhDs that we fund, we basically,

in some cases we fund what are called
doctoral training partnerships or a bunch

of universities get together and say we
are going to bid to run social science

PhDs in the east of England, for example.

And then they allocate the PhD
places within their universities.

So their bid will sort of give some
idea about what they're going to do,

but it's quite considerably within the
power of the academy. And then in some

other cases we will set up what are
called doctoral training centres,

centres of doctoral training where we
sort of say we want to focus on let's say

applications of AI in the social
sciences or applications of advanced

quantitative methods
in the social sciences.

And there we'll be more hands-on and say
we specifically want people to focus on

these kind of areas. We'll work with
supervisors who work in that area.

Most of what we do is in the first
category. And it's a interesting question,

should the government be
controlling that more? Should we be,

do we think universities
are good at making those
allocations or is that kind of

a victim of internal
academic politics? It.

Feels like why is government any better
or why is the ESRC any better at doing

that?

I think it depends a little bit on what
you think about what the incentives are

in universities to allocate.
We've certainly got,

as a public funder, we've got some broad
government incentives to fund things,

which probably not a million miles out
of line from what most people would have.

Economic growth
Solving,

relatively big general problems
that are of importance to voters.

Obviously governments can
get lots of things wrong,

but there's some ultimate link between
what governments do and what citizens

want when it comes to what
universities fund. On the one hand,

universities have obviously got a
public mission and they will no doubt be

thinking about those kind of
things. But at the same time,

there's a question of how much of this
is governed by internal university

politics and just the
balance between departments.

So it's something I'm looking at.
I'm just curious about how we do it.

I guess the real question is if
you're funding someone to do a PhD,

you ideally want to reduce the chance
that they are going to regret spending

those years of their life studying that.

So you want to make sure that they are
gaining useful skills in the way we do

when we think about university degrees.

So that's kind of what we're
trying to optimise for.

Here's a stupid question,
which I dunno the answer to,

and probably I should look up rather than
asking an expert who happens to be in

the room with me.

But I assume that you can't earn
a PhD while working anywhere but a

university. Is it the case that you,

before doing any valuable
research need to have,

you need to have worked at
a university to get a PhD?

Should that be the track
of all researchers?

So that's a super good question. I mean,

one of the things that a couple of years
ago we reviewed all our social science

PhDs and sort of thought, well,
what should they look like?

And one of the things we made compulsory
was everyone's got to spend a few

months working somewhere other than a
university, which is in a sense kind of

recognising the truth
in what you're saying,

that the source of all wisdom is
not going to be within universities.

You do get, particularly in kind of the
sciences, you get more industrial PhDs,

you get people actually doing their PhD
while working in a business more rare.

But it's definitely doable if you have
the right kind of supervision structure.

But I think it feels to me like it
will be a good thing to do more of.

It'll be a good thing to get more
organisations that are not universities

able to provide the kind of training,

because I guess we know that
organisations provide really,

really good training in lots of
other fields of life. I mean,

I started my career at McKinsey,

which is a place that trained
people in a pretty mechanical,

rigorous way and generated certain types
of skills that were quite transferable.

It doesn't seem to be beyond the whit
of man that other places could be doing

that and build useful research skills.

I was imagining we talked about ARIA at
the beginning and then also what you do,

which I think of as
being university science.

But there are other kinds of organisations
that aren't necessarily taking crazy

bets like Moonshot ARIA choices,

but also aren't necessarily universities
like Lawrence Livermore National Lab or

Max Plan Institute or something like that.

I was wondering what you thought about
having more of that in the research.

Yeah,

so this is a really interesting thing
more broadly because the UK is kind of

weird among rich countries in the amount
of our publicly funded research that

goes through universities with
most other rich countries,

Germany, the us, France,

a much bigger chunk of the publicly funded
research that they fund goes through

national labs or other organisations
that aren't universities. And

my prior is that

that institutional diversity
is probably quite good.

It's probably good for the system.

And I think there's a
couple of reasons for that.

I think the first thing
is that they often,

these national labs and other
organisations often have more of a

focus on certain practical outcomes.

They're often quite good at transferring
things. I mean, in the social sciences,

the biggest non university organisation
that we fund is the Institute for Fiscal

Studies,

a UK organisation that does amazing
economic analysis of public policy,

hugely impactful. They basically
help define the fiscal framework that

the UK uses. You can quibble with whether
that's a good fiscal framework or not,

but it's very much the result of
decades of work and analysis by them.

But they're very focused
on practical application.

They're very focused on talking to
the media, on talking to politicians.

And as a result,

they do work that is very well
oriented towards those kind of people.

And it makes you think if you
are someone who is training there

and people who trained at the IFS work
in all sorts of interesting roles,

both in academia and in the real
world and business and government,

you learn a very different
set of skills, I think,

than you would in a
classic university PhD.

Well, look, I was at the ARIA Summit
this week. It was very interesting,

very exciting, lots of really cool work.

But it did make me think how
can they possibly, how can we,

it's going to take us 30 years before we
can look and say whether this succeeded

or not.

And I feel that this is true of almost
all of the money that we spend on

research, unless it's really,
really, really useless research.

There's an inverse correlation between
how soon you can measure the impact

of the research and how worthy it was
to have funded in the first place.

Because really what you want
is the massive long-term bets,

and you really do want that really
long-term investment in smart people and

ideas and research and infrastructure
and so on. But it does make you think,

are we just potentially just
throwing money into gaping more?

I don't think we are with ARIA. I
don't know that we are with the ESRC,

but I don't know that I could answer
definitively that we're not because what's

the counterfactual?

It's really hard to measure.

I think economists have been
wrestling with this for a long time.

I think we'll continue
to wrestle with this.

We've been having some really interesting
conversations with Open philanthropy

about how we might be able to
analytically push the frontier on this.

I guess what I would say is there are
definitely some research and development

bets that are really long-term, like
you say, the kind of mRNA vaccine work.

You start work in, I dunno, 1980.

And.

It yields the benefits in 2020
when there's a COVID pandemic.

Some of that stuff is really, really
long term. And for a long time,

as we know with mRNA vaccines,
people thought this is a blind alley.

This is a really low
status, low return field.

There's definitely some of those
kind of high vARIAnce bets.

But when I look at the stuff that we fund,

there is some stuff that generates
results quite quickly. I mean,

not of the scale of saving the
world from a deadly pandemic,

but stuff that's genuinely really
useful in a more short, measurable term.

So project that we've been running
for, we've been funding for a while,

which goes by the name of
the decision maker panel,

is basically an economic project to kind
of work out what's going on with people

who run businesses. And
it's run partly in the UK,

partly in Stanford.
So Nick Bloom, who you may know,

Stanford Economist is very involved in it.

And they basically just found a better
way of more rapidly surveying businesses

to ask them questions about the economy.

It turned out that was really
useful immediately post
pandemic because they were

the people who did all these really
detailed surveys on working from home.

So you might have seen the
headline figures that Nick,

sometimes he talks about them
quite eloquently on Twitter,

where they basically said that
hybrid working can be as good

as in-person working,

but you've got to be in the
office at least three days a week.

And those three days have to be the same
as your colleagues, which is kind of,

no one really knew.

And there was something that people
were hugely speculating about,

and Nick brought data that was a kind of
big research project that would've been

pretty hard to do otherwise,

would've been pretty unlikely that
a business would've funded it.

And the return was definitely within
five years, probably shorter than that.

So there's definitely some stuff that
has a quicker return and you see the

benefits more incrementally. But I
agree there's a real challenge about

how do you measure these
really big long-term bets?

Well, an even pointier version of
that would be, so if I asked you,

should we do more of what you
do, you'd probably think, well,

what we do is amazing. You
should definitely do more.
We're not at that point,

but how will we actually know we are at
the point where we are about to spend

too much or about to spend too
little? Whereas what could we do?

What would you actually do if I told
you tomorrow I'm Keir Starmer and

you have to decide exactly how much there
is with a really strong argument for

why it's that number, how would
you try and do that? What.

Would be the optimal amount? So I
think this is a really tough one,

and part of the problem is, I mean,

there's a question about
how do you work out,

where do you hit diminishing marginal
returns, but there's also a problem about,

for want of a better word,

what's the kind of heterogeneity of
the returns to an R&D investment.

So if you imagine the kind of world,

the sort of magical library where you
can see every R&D project that you funded

and each one is kind of
in discrete little blobs,

and then you can magically
see what the value, the end,

end result value of those investments is,

how close to the average you going to be?

How grouped are they going to be or are
there basically being a few things that

are like the mRNA vaccine that are
incredible home runs that massively have a

huge ROI and others that
don't? And I guess if we think

about physical investments,

if we think about buying a fleet
of vans for a business that runs a

delivery business, if you
pay $20,000 for a van,

that van is going to be worth about
$20,000. Some vans are lemons,

but the clustering is going to be
very tight. Partly are mass produce,

partly because they're tradable goods.

There are markets for means
you can determine the price.

That kind of capital is pretty
homogeneous in its value R&D assets

intuitively, you think they're
going to be much more heterogeneous,

they're going to be much more random.

So I guess what that means is if you've
got a choice between optimising on

two dimensions, increasing the
quantity and increasing the quality,

at some point, if you genuinely
think you can increase the quality,

if you think that funding science in a
better way will allow you more likely

to get those home runs,

then maybe you want to focus more on
optimising the quality rather than

optimising the quantity.

I'm not going to name any institution
because nobody's here to defend

themselves, and I don't want to ask you
to defend or criticise any institution.

But I have often seen institutions
that I think are putting out basically

politicised nonsense, let's
say about housing for example,

but not limited to housing that they
have been in receipt of ESRC funds.

And the same is true in
lots of other countries.

It's not a criticism of your
organisation in particular,

but it seems to be the nature
of the further you veer from

the hard sciences into let's say the
social sciences or the humanities,

the closer you get to funding people's
political ideological hobby horses.

And that's fine everybody.
I mean, I've got plenty,

but I don't think that it's good.

I don't think it's the right
way to use taxpayer money.

And I think it's just bad.

It creates a negative externality to
fund bad research and to fund politicised

research. So how do you avoid
that or do you avoid that?

Is that just a lot of academics seem to
think this is part of the deal that they

get funded by the government to do the
thing that they are being contracted for,

let's say,

and then in their free time they get to
write pieces about how you don't need to

build any more houses,

you can just redistribute people up to
the Scottish Highlands and there are

plenty of houses there. Is
that a problem in your mind?

So I think it is a problem,

but I think I might be seeing a
different problem to the one that you are

seeing. So for me,

the fact that researchers are
going to have ideological priors,

I'm actually not so bothered
by just that very fact.

I think there's a pretty noble
tradition of people coming up with very

insightful social science
when they come from a very,

very strong ideological position.

And it's also pretty hard to drive
those priors out of the system.

What I think is a problem
is if those ideological

priors aren't worked out in the
way research comes together,

in the debate between research and in the
quality control mechanism that happens

in academic debate or public policy
debate around that academic work.

And I guess where that becomes a problem
is if you've got systematic bias in the

researcher base. To me, if you've

got someone who has a very
strong ideological bias towards

the kind of position you're describing,

a kind of NIMBY redistribute
people around the country position,

the problem is if that represents kind
of an overwhelming majority of opinion,

say because of the class interests of
the people who are doing the research and

that then the overall body
of research is effectively

skewed. And I guess the question
is how common do we think that is?

There was some really interesting,
well, survey research done. I mean,

John Haidt in the US did quite a lot of
it looking at the academy a few years

ago. There's been some
really interesting research

in polling research in
the UK by more in common,

in fact looking at segmenting
people by ideological opinion.

And that seemed to suggest,

which probably won't surprise people
that in the academy there are kind of

ideological biases.

And I guess the question is that
probably doesn't matter that much

for the majority work. I mean,

the majority of research that's done
in the academy is hard sciences,

life sciences, medicine. And
although some of those things,

your ideological priors matter for a
lot, it doesn't really matter. I mean,

I would argue that if all

material scientists were fervent Albanian
nationalists probably wouldn't make

much of a difference because the two
things don't intersect very much.

But as you say,

if every economic geographer has
some sort of particular ideological

prior that's not related to their work
about the egalitarian distribution of

land, that probably is a problem. And
that's why maybe in the social sciences,

maybe in the arts and humanities,
we have to worry more if the academy

is systematically ideologically biassed.

And I guess some of John
Hay's work suggested that
those biases are growing over

time,

probably reflects slightly the different
experience of working at university

over that time. And I guess
that for me is really,

that is something that we still be
concerned about and we still be trying to

say, well,

if we want the optimally truth
seeking research landscape,

then we have to pay
attention to that as funders

and make sure that you are getting an
appropriate debate about these issues.

That's not just purely being driven by
a particular distribution of views among

the researchers you're funding.

Thanks for listening. Check out
Works in progress@worksinprogress.co.