What GDP Doesn't See — Rabbit Holes

Yet another interesting debate on the limits of GDP, this time triggered by David Deutsch posting about fixing his dishwasher with ChatGPT, and Jesús Fernández-Villaverde riffing on what that means for GDP, welfare and taxation.

On X · @DavidDeutschOxf

On X · @JesusFerna7026

Amen to this:

On X · @DavidDeutschOxf

On X · @krishnanrohit

This is one of those debates that keeps coming back in economics because everybody knows GDP has obvious limitations, and yet nobody has really managed to replace it.

The funny thing about GDP is that for something so crude, it is annoyingly useful.

Lant Pritchett has made this point quite well. Economists obviously don’t think GDP is a direct measure of wellbeing, and he readily acknowledges all its limitations. But, as he puts it:

His broader point is that sustained increases in productivity and income tend to be associated with improvements in most of the basic things we actually care about: poverty, health, education, sanitation and so on.

So GDP is simultaneously a terrible measure of lots of things we care about and an extremely difficult measure to beat. That line is mine, by the way, not Pritchett’s.

But its limitations manifest themselves in wonderfully weird ways.

Suppose a country is at war and starves large parts of its civilian economy of resources to ramp up the production of missiles, shells, guns, tanks and every other kind of armament. All of that military production counts towards GDP. Measured GDP can therefore rise even while ordinary people are consuming less and, quite plausibly, becoming worse off.

This isn’t some new critique invented by people arguing about AI. Simon Kuznets, one of the fathers of modern national-income accounting, was wrestling with almost exactly this problem nearly 90 years ago.

In his famous 1934 report to the US Congress, he warned:

There is a useful discussion of that warning and the evolution of national-income accounting in this NBER paper.

But Kuznets went much further than the usual “GDP is not welfare” disclaimer.

In a 1937 discussion published by the NBER, he wrote:

You can read the original NBER chapter here.

That is a remarkable passage for something written in 1937.

Kuznets wasn’t saying that armaments, advertising or financial activity somehow weren’t economic activity. He was asking a harder question: does every dollar of measured economic activity represent an equivalent increase in human welfare?

Clearly not.

There is also a historical irony here. Part of what makes GDP look strange as a measure of human progress is that national accounting was shaped partly by a very different practical problem: how much can an economy produce? During a war, the capacity to produce tanks, aircraft, ammunition and ships matters enormously even if household consumption is being squeezed.

Diane Coyle, in her excellent GDP: A Brief but Affectionate History, gives another wonderfully absurd example.

A widower employs a housekeeper and pays her a salary. Her work is market activity and therefore contributes to GDP.

He marries her.

She continues doing exactly the same household work, except now she isn’t being paid for it.

GDP falls.

Nothing necessarily happened to the quantity of useful work being done, and their welfare need not have fallen by a rupee. An activity simply crossed the accounting boundary between market production and unpaid household work. There is a nice discussion of the example in this IMF review of Coyle’s book.

Which brings us back to AI and David Deutsch’s dishwasher.

In the old world, your dishwasher breaks. You call a technician. He fixes it. You pay him ₹2,000. That transaction is part of measured economic activity.

In the new world, the dishwasher breaks. You show ChatGPT the problem, it figures out what’s wrong, tells you what to do, and you fix it yourself.

You have a functioning dishwasher. You have saved ₹2,000. You may even have learned something.

But the repair transaction has disappeared.

Strictly speaking, GDP doesn’t necessarily fall because David Deutsch repaired his dishwasher. GDP is simply lower than it otherwise would have been if he had paid someone to perform the same service.

And this is where I think AI makes an old measurement problem much more interesting.

The same thing already happens with books. If Jesús Fernández-Villaverde buys a book, the production and sale of that book are captured in GDP. The author gets paid, the publisher gets paid, Amazon gets its cut, etc.

What isn’t captured is the full value of the knowledge he acquired.

Maybe a $20 book teaches him something that saves him hundreds of hours over his lifetime. Maybe an idea changes an important decision and makes him enormously better off. GDP doesn’t suddenly record the value of that knowledge merely because it originated in a market transaction.

AI could make this wedge between what we pay and what we get much, much larger.

For a few dollars a month, or perhaps eventually almost nothing, you could have something that helps you repair appliances, learn maths, understand a difficult paper, debug code, translate documents, learn history, analyse data, write, think through decisions and do dozens of things for which you previously needed either another person or years of accumulated expertise.

A lot of the value might therefore show up as higher consumer surplus rather than proportionately higher measured GDP.

There is actually an interesting attempt to measure precisely this sort of gap.

Erik Brynjolfsson and his co-authors have spent years trying to estimate the value of digital goods that conventional national accounts largely miss. The basic idea is simple: instead of asking what you paid for something, ask how much you would have to be paid to give it up.

In one set of experiments, respondents valued access to search engines at a median of about $17,530 a year, email at $8,414 and digital maps at $3,648. Because many of these services are free at the point of use, much of that value is consumer surplus rather than expenditure captured directly in GDP. The study is here.

Brynjolfsson and his co-authors later proposed a supplementary measure called GDP-B, with the “B” standing for benefits: not a replacement for GDP, but an attempt to account for welfare created by new and free goods.

And a larger 2023 study covering ten digital goods across thirteen countries estimated more than $2.5 trillion a year in consumer welfare, roughly 6% of those countries’ combined GDP. Interestingly, it found proportionately larger welfare gains among lower-income people and lower-income countries. That paper is here.

This raises a broader question that goes well beyond AI.

What is the economic value of all the things we get for free?

On X · @greg_ip

Take Google Search, YouTube, email, maps, Wikipedia or any number of free digital services. Obviously the companies behind many of these products are not economically invisible. They employ people, buy servers, sell advertising, make profits and pay taxes, and all of that shows up somewhere in the national accounts.

But that is not the same thing as measuring the value these products create for their users.

And yes, big technology companies create harms too. Algorithmic manipulation, privacy loss, effects on communities and politics, mental-health concerns and all the rest are real questions. If you wanted to do some impossible moral accounting of the whole thing, you would have to put the benefits on one side and the negative externalities on the other.

My point is narrower: the value of a free service to its users is not zero merely because its price is zero.

Now take the idea one step further and think about open-source software.

Linux is free, and in one form or another it sits underneath an absurd amount of the world’s digital infrastructure. The same is true of PostgreSQL, Python, Git, OpenSSL and thousands of other projects.

The economic activity built using open-source software eventually shows up everywhere: cloud computing, banks, websites, software companies, salaries, profits, taxes and so on.

But where exactly is the value of Linux itself?

Imagine two otherwise identical worlds.

In one, every company pays “Linux Corporation” $100 billion a year to use Linux.

In the other, exactly the same software does exactly the same job but is freely available as open source.

Measured market transactions would be larger in the first world. It isn’t obvious that humanity would be better off.

In fact, we would probably say the opposite. Making an enormously useful input essentially free has made society richer by freeing resources for other things.

This is perhaps another version of the housekeeper problem. Diane Coyle’s housekeeper moves from paid work to unpaid work. Linux moves something from a proprietary market transaction into a commons. David Deutsch moves dishwasher repair from a paid service into something he can do himself with freely available knowledge.

AI could cause millions of activities to cross that boundary at once.

There is another place where critics of GDP are on even stronger ground: the environment.

Imagine a factory that burns enormous quantities of coal and produces a million widgets. The widgets are sold, workers get paid, the company earns profits and the government collects taxes. All of that economic activity shows up in GDP.

What doesn’t automatically appear as a deduction is the carbon released into the atmosphere, local pollution or the damage those emissions may impose on people somewhere else or decades later.

Or take an extreme example. Clear a large part of the Amazon, sell the timber, build factories on the land, employ thousands of people and raise their wages. GDP could increase substantially. Material living standards in the region might improve too.

But something else has happened at the same time: an enormous stock of natural capital has been destroyed.

The accounting analogy here is useful. GDP is a little like looking at a country’s income statement without looking closely enough at its balance sheet. You can make this year’s income look better by consuming an asset.

The UN itself uses almost exactly this forest example when explaining its System of Environmental-Economic Accounting: cutting down all of a country’s forests could increase GDP in the short run through timber production while destroying natural wealth and imposing enormous long-run costs.

Economists and statisticians are perfectly aware of this problem. The UN now has a formal framework for ecosystem accounting. There are also attempts at “Green GDP”, which deduct resource depletion and environmental degradation from conventional economic measures. The World Bank publishes Adjusted Net Savings, which takes net national savings, adds education expenditure, and subtracts things such as energy depletion, mineral depletion, forest depletion and carbon and particulate pollution damages.

But once you try to do this properly, the measurement problems become brutal.

What is a rainforest worth? What is the value of an extinct species? What number do you put on a stable climate, clean air or an ecosystem that prevents floods? What discount rate should we use for damage imposed on someone born seventy years from now?

There probably isn’t a neat answer.

And then there is one final weirdness. Environmental damage can sometimes generate measured economic activity when we cause it and more activity when we repair it. Pollution creates output. Treating some of the illnesses associated with pollution creates output too. A natural disaster destroys homes; rebuilding them generates output.

None of this means GDP is fraudulent or useless. It means GDP isn’t keeping a moral ledger in which it records factory output on one side and subtracts damaged lungs, depleted aquifers or lost forests on the other.

There have been endless attempts to go “Beyond GDP”. A 2024 review in The Lancet Planetary Health went through 65 different alternative metrics developed across roughly five decades of work. Despite all of these proposals, their integration into actual policymaking and public discourse remains limited.

That, in a way, is the punchline.

I realise some of this can sound like the usual rant about the inadequacy of economics or the absurdity of reducing everything to GDP. That isn’t really my point.

GDP is useful. Income growth is useful. GDP per capita is useful. Part of the reason these measures have survived for so long is that they often do a remarkably good job of summarising a vast amount of economic reality in a single number.

The problem, I think, is that most of us don’t stop to ask what exactly is being counted, how it is being counted and, perhaps most importantly, what isn’t being counted at all.

There is a famous line, usually misattributed to Einstein, but apparently due to the sociologist William Bruce Cameron:

The attribution is discussed here.

In a peculiar way, I think we all suffer from a kind of economic blindness.

When we talk about human progress, we naturally reach for the broad numbers that are easiest to see: GDP, GDP per capita, income growth, productivity and so on. Most of the time these are useful shortcuts. But they are still shortcuts.

They can tell us an enormous amount about market production. They are much worse at telling us how much knowledge has become freely available, how much consumer surplus has been created, how much unpaid work is being done, how much natural capital has been destroyed, how much pollution has been imposed on somebody else, or whether all of this has actually translated into better lives.

This doesn’t mean GDP has served its purpose and should be discarded. If anything, it means we have reached the limit of what we should ask it to tell us.

At the very least, economic progress should probably be thought of as an ensemble rather than a scoreboard: production and income, yes, but also health, education, distribution, leisure, environmental wealth, sustainability, consumer welfare, perhaps access to knowledge and other things that are becoming increasingly important in a digital economy.

The difficult part, of course, is that the moment you move beyond GDP, measurement becomes much messier. There is no obvious exchange rate between a forest and a factory, between an extra year of healthy life and another percentage point of income, between free access to human knowledge and the harms created by the platforms providing it.

Perhaps that messiness is precisely the point.

GDP survived partly because it gives us an extraordinarily clean answer to a relatively narrow question.

Human progress is not a narrow question.

On X · @GestaltU

This short note was written with the help of ChatGPT, based on a back-and-forth about the economics, the historical context and the underlying sources.