Accounting for free goods in GDP, and the economic value of generative AI

In a recent Wall Street Journal article (ungated version here), Avinash Collis (Carnegie Mellon University) and Erik Brynjolfsson (Stanford University) report that:

In late 2024, a nationally representative survey of U.S. adults revealed that 40% were regular users of generative AI. Our own survey found that their average valuation to forgo these tools for one month is $98. Multiply that by 82 million users and 12 months, and the $97 billion surplus surfaces.

This estimate of $97 billion per year provides a measure of the economic impact of AI. That is about 0.33 percent of US GDP (which was about $29.3 trillion in 2024). That is somewhat less that I would have expected. However, to put that $97 billion in context, it is nearly the same size as the 'value added' (the industry-level equivalent of GDP) of the entire motion picture and sound recording industry (which was $119 billion in 2024).

Comparisons such as that may not be sensible though, because we aren't quite comparing apples with apples. GDP is really a measure of production, whereas the value generated by ChatGPT estimated by Collis and Brynjolfsson is closer to a measure of consumer surplus. ChatGPT does contribute to GDP already of course, because each user who has a paid account pays for access. However, what they pay is far less than the value they receive from access to ChatGPT. And some consumers are paying nothing at all.

This problem, and a potential solution, are outlined in this new article by Brynjolfsson, Collis, and co-authors, published in the American Economic Journal: Macroeconomics (ungated earlier version here). They explain the problem as follows:

New, sometimes very specialized, goods appear with increasing rapidity... and digital goods (such as information and entertainment services) are increasingly available at zero price, reflecting their very low marginal costs of replication and distribution... the positive quantities of these goods that are consumed have a measured price of zero and measured value of zero in the conventional national accounts even if they create considerable consumption value for consumers. A related difficulty arises in the valuation of new goods, since there is no observed price for the period before their appearance. Despite the increasing relevance of new and free goods, the value to consumers is not reflected in standard statistical agency reports for GDP or derivative metrics like productivity, which are typically defined in terms of GDP.

Brynjolfsson et al. provide a framework for estimating the welfare contribution from new zero-priced goods, as well as the quality improvement of existing goods. The framework itself is quite mathematical and not for the faint-hearted. However, the basic premise is that the welfare that is generated by a good that is offered for free can be estimated by estimating how much consumers would be willing to accept to give up access to that good for a period of time (notice that this is what Collis and Brynjolfsson talk about in their WSJ article in relation to generative AI).

There are various ways that can be used to estimate what consumers would be willing to accept to give up a free service. However, the challenge is that the estimates need to be credible. Brynjolfsson et al. provide two examples of incentive-compatible experiments. In these experiments, the research participants might really have to give up the service they were being asked to value, which provides a strong incentive for them to provide their 'real' valuation of what they would accept. The first experiment was conducted online and used to value Facebook (this is research that I blogged about back in 2018). In this case:

In the experiment, each participant was asked to make a single discrete choice between two options: (i) keep access to Facebook or (ii) give up Facebook for one month and get paid $E. We allocated participants randomly to 1 of 12 price points: E ∈ {1, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1,000} —that is, we observe at least 200 participants per price point. Before participants made the decision, we informed them that their decisions were consequential such that we would randomly pick 1 out of every 200 participants and fulfill that person’s selection. We also informed them about how we can monitor their Facebook online status remotely. In order to check if the selected participants gave up Facebook and qualified for the payment, we monitored their online status on Facebook for 30 days...

Research participants were only paid if they didn't log onto Facebook for the 30 days. In their second example, Brynjolfsson et al. conducted a lab experiment with students in the Netherlands. In this case:

We asked participants to state the minimum amount of money they would request in order to give up their smartphone camera (both main camera and front camera) for one month. Participants were informed that this amount would serve as a bid in a lottery. If their minimum bid to forgo their camera would be higher than a random price, drawn from a uniform distribution, they could keep access to their smartphone camera but would not receive any cash...

In order to induce incentive compatibility and make the answers consequential, we provided further information that 1 out of 50 participants would be selected for the lottery and that we would block their smartphone cameras with a special sealing tape if their bid was successful... The sealing tape would break if the participants tried to peel it off so that it was not possible to reapply it. We also signed the tape so that it was not possible to buy the same type of seal and reapply a seal. If, after the one-month period, the original seal was still intact participants were rewarded with the money and the seal could be removed.

Notice that in both cases, the research participants might really have to give up what they are being asked to value. Collis and Brynjolfsson no doubt did something similar to derive their estimate of the value of generative AI.

Anyway, coming back to the Brynjolfsson et al. paper, their purpose is to create a new measure, which they term GDP-B, that includes the benefits of goods and services that have high marginal value to consumers, but are offered at low or no cost to them. This is not limited to the particular examples that Brynjolfsson et al. cite (which include not just Facebook and smartphone cameras, but also Instagram, Snapchat, Skype, WhatsApp, digital maps, LinkedIn, and Twitter). Even that list is very incomplete of course. 

And, given that every good or service generates consumer surplus, the approach could be extended to every good or service. No doubt that would be the ideal, so that GDP-B captures the consumption benefits of all goods and services. However, the data collection task required to estimate consumer value for every good and service would be enormous, dwarfing the efforts already taken to measure the Consumer Price Index (which doesn't survey the price of every good and service).

Adopting an approach that only accounts for some goods and services seems to me to be suboptimal. And that is what makes the comparisons a bit problematic. Brynjolfsson et al. compare traditionally-measured GDP growth with growth based on their measure GDP-B, which includes the benefits from Facebook (or smartphone cameras). However, all they can really show there is that growth is higher when the benefits from Facebook (or smartphone cameras) are included. I would take the question of how much higher growth is with a grain of salt - they aren't accounting for the benefits of all of the other goods and services that they haven't valued in the same way (for some of which, the benefits might have declined, because consumers value them less, leading to lower growth).

None of this is to say that we shouldn't be finding better ways to measure welfare than GDP, which has long been acknowledged as a very incomplete measure. Brynjolfsson et al. have provided a measure that goes beyond GDP, which is what many have been calling for, for some time.

[HT: Marginal Revolution, here for the WSJ article, and here for the AEJ:Macro paper]

Read more:

• How much money would you accept to give up Facebook for a month?

Natural capital and the problematic measurement of GDP

I've been thinking a bit about GDP this year, and in particular about the weirdness of its measurement. One of the key problems that has occupied me has been an asymmetry in how capital is accounted for within GDP. When new capital is created, the spending on the new capital adds to GDP. However, when capital is depleted, that depletion does not subtract from GDP. That is why, following a large natural disaster, GDP might actually increase due to rebuilding activity (and because any destruction of capital is ignored).

With that in mind, I was interested to run across this 2019 article by Colin Mayer (Oxford University), Published in the journal Oxford Review of Economic Policy (ungated earlier version here), deep down in my to-be-read pile of articles. Mayer was a member of the UK's Natural Capital Committee, which ran from 2012 to 2020, and this article considers how economists can, and should, approach accounting for natural capital. Mayer distinguishes between economists' traditional view of natural capital, and an approach more similar to how an accountant would approach natural capital:

To the economist, natural capital, like any other asset, is the plaything of humans, there to be treated as mankind sees fit. To the accountant, the firm is an entity of which the managers are the stewards. They are there to preserve the firm and to promote its flourishing. So, too, we should consider whether it is our right to employ nature in the way in which we see fit, or our obligation to act as its steward or trustee.

Mayer's solution is that we should revise how natural capital is treated, and should:

...incorporate a maintenance charge in the balance sheets and profit and loss statements of nations, municipalities, corporations, and landowners to reflect the liability associated with maintaining or restoring these assets.

I think that Mayer could have been much clearer in the explanation here. When natural capital is depleted, through pollution, or extractive industries, or carbon emissions, my view is that the cost of that depletion should directly reduce GDP (which is the equivalent of the 'profit and loss statements' that Mayer refers to). Instead, Mayer seems to be suggesting that this is a liability. Both of those approaches may be correct, given the simple accounting identity (Assets + Expenses = Liabilities + Proprietorship + Revenues). A liability on the right-hand side of that identity equation can arise because of an expense on the left-hand side. However, the labelling as a liability implies an obligation to repay, which may not be the case for all types of natural capital (how would one pay off the liability of mining extraction, for instance?).

Anyway, there is clearly more thinking to be done here. I don't think that economists' approach to natural capital is correct. I think that the approach to other forms of capital (physical, social, and human capital) is similarly flawed. For example, decreasing social capital over time (as accounted by Robert Putnam's 2000 book Bowling Alone (which I reviewed here) should also decrease GDP in my view. By correctly accounting for changes in capital (both upwards and downwards) GDP would better capture changes in societal-level wellbeing.

Noah Smith on why imports do not subtract from GDP

I am not a macroeconomist. Against my protestations, I have taught macroeconomics in the past, but now I exclusively teach microeconomics. There are certain aspects of macroeconomics that I thought I knew well, like how GDP is calculated. There is a simple method of calculating GDP that we teach in first-year economics, which we call the expenditure method: Y=C+I+G+(X-M). Y is GDP, C is consumption spending, I is investment spending, G is government spending, X is exports, and M is imports. It all seems rather straightforward. However, I genuinely learned something new and important this week about that formula.

Noah Smith has a great post explaining why imports do not subtract from GDP. Check the formula above, and then read that sentence again. Imports do not subtract from GDP. But it's right there in the formula! The thing I learned from Noah's post is that imports are included in C, I, and G. And so, the subtraction of M in the expenditure method formula prevents us from counting imports in measured GDP, by zeroing them out. Imports are not subtracted from GDP. Because they are both added to GDP (through C, I, and G), then subtracted (through -M), the net effect of imports on GDP is zero.

As further explanation, it is worth quoting Smith's post at length (the strikethrough and underline in one of the formulas is my correction of it):

Let’s talk about what GDP is. GDP is the total value of everything produced in a country:

GDP = all the stuff we produce

Imports aren’t produced in the country, so they just don’t count in the formula above. And they aren’t alone. There are plenty of other important things in the Universe that have don’t get counted in GDP, simply because they have nothing to do with domestic economic production. The number of asteroid impacts in the Andromeda galaxy is probably important to someone, but it doesn’t count in U.S. GDP. The population of the beluga sturgeon in Kazakhstan is probably important to someone, but it doesn’t count in U.S. GDP. Imports don’t count in U.S. GDP because, like asteroid impacts in the Andromeda Galaxy and the population of beluga sturgeon in Kazakhstan, they don’t involve domestic economic production in the United States.

In fact we can divide GDP up a different way from the Econ 101 breakdown. Let’s divide it up according to all the categories of people who might ultimately use the stuff... we produce in the U.S.:

GDP = Capital goods we produce for companies + Consumer goods we produce for consumers + Stuff we produce for the government + Stuff we produce for foreigners

Again, imports are nowhere to be seen. But exports are in here! Exports are just all the stuff we produce for foreigners. So the formula is:

GDP = Capital goods we produce for companies + CapitalConsumer goods we produce for consumers + Stuff we produce for the government + Exports

This is a perfectly good formula for GDP. But instead, here’s what economists do. They add imports to the first three categories, and then subtract them again at the end:

GDP =

(Capital goods we produce for companies + Capital goods we import for companies)

+ (Consumer goods we produce for consumers + Consumer goods we import for consumers)

+ (Stuff we produce for the government + Stuff we import for the government)

+ Exports - Capital goods we import for companies - Capital goods we import for consumers - Stuff we import for the government

This type of equation adds in three different types of imports, then subtracts them all again at the end. It’s mathematically equivalent to the formula above it, because if you add imports and then subtract them out again, you’ve just added 0. And adding 0 does nothing. Imports still don’t count in GDP in this equation.

OK, now let’s realize what the terms in the equation mean:

(Capital goods we produce for companies + Capital goods we import for companies) is just Investment.

(Consumer goods we produce for consumers + Consumer goods we import for consumers) is just Consumption.

(Stuff we produce for the government + Stuff we import for the government) is just Government purchases.

Exports - Stuff we import for companies - Stuff we import for consumers - Stuff we import for the government is just Exports - Imports.

So the equation is now:

GDP = Consumption + Investment + Government purchases + Exports - Imports

This is just our good old Econ 101 equation. It looks like imports are being subtracted from GDP, but now you (hopefully realize) that this is because imports are also being added to consumption, investment, and government purchases! Consumption, Investment, and Government purchases include imports, so we subtract out imports at the end so that the total effect of imports on GDP is zero.

Smith leverages that explanation to explain why a focus on reducing imports will not increase measured GDP (at least, not directly). That is an important argument in an era of increasing trade protection, aimed at reducing imports to the benefit of the domestic economy. That trade protection is not likely to work - at least, not through the simple mechanism of reducing something that is subtracted from GDP. Because, as Smith tells us, imports are not subtracted from GDP.

[HT: Marginal Revolution]

Taxes are not part of GDP

Our Prime Minister doesn't know the difference between GDP and the government accounts. That much is clear from her slip-up last September. However, she can almost be forgiven for that. After all, she did a communication studies degree, which almost certainly didn't include any economics. And she isn't finance minister. However, I would expect business reporters to know better. From Aimee Shaw in yesterday's New Zealand Herald:

The beer industry contributed $646 million to GDP in the year to March 2018, made up of $331m in GST and $315m in excise tax.

That sentence is exactly wrong. GST and excise tax do not contribute to GDP. To see why, let's start with the definition of GDP: The market value of all final goods and services produced within a country in a given period of time.

There are three approaches we can use to measure GDP: (1) the expenditure approach, which adds up all of the spending in the economy; (2) the income approach, which adds up all of the income in the economy; and (3) the production approach, which adds up the value of everything produced in the country. All three of these should (in theory) add up to the same value. This is easiest to see for the expenditure and income approaches, since every dollar of spending by Person A must become income to Person B.

To see why GST and excise tax are not part of GDP, let's start with the production approach. The idea is to add up the value of everything produced in the country in the last year (or quarter). So, you add up every good and every service produced in that time, and multiply each of them by their market price. The market price is the price excluding GST or excise taxes. The reason they are excluded is simple - they don't affect the underlying value of the good or service. If you included GST or excise taxes in the measure of the value of goods and services, then the government could artificially inflate GDP every year by increasing GST. So, GST and excise taxes are not included in GDP.

The expenditure approach adds up all of the spending in the economy, including spending by households (consumption), spending by businesses (investment), and spending by government, with an adjustment for net exports (the difference between the amount that overseas countries spend on goods produced in New Zealand (exports), and the amount that New Zealand spends on goods produced overseas (imports)). Again, there is no room for GST or excise tax in there.

The income approach adds up all of the income in the economy, including income from labour (wages), income from capital (rents), income from savings (interest), and income from entrepreneurship (profits). Notice there is no role for GST or excise tax in there either.

Taxes are part of the government accounts, and the difference between taxes and government spending is the budget surplus (if taxes are larger than spending) or deficit (if taxes are less than spending). Our Prime Minister might not know the difference, but we should expect better of the business media.