Beyond GDP: Rethinking productivity in today’s economy

Garreth Hanley:
Welcome to INTHEBLACK. In today's episode, we're talking to Professor John QuiggIn about productivity. We'll be discussing alternative methods for assessing productivity in today's economy, what productivity means in an age of rapid technological advancement, and if traditional measures like gross domestic product, GDP, and multi-factor productivity, or MFP, are still relevant in a globally interdependent and digital interconnected economy.

Professor QuiggIn is a professor of economics at the University of Queensland and a fellow of the Econometric Society. He has over 1,500 publications, including 10 books and over 200 refereed journal articles, spanning decision theory, environmental economics, production economics, and the theory of economic growth.

Professor QuiggIn's work has been cited over 23,000 times and has a H-index of 68, and his latest book, After Neoliberalism, was released in 2024 by the Australian National University's ANU Press.

Welcome to INTHEBLACK, John.

Prof John Quiggin:
Glad to be here.

Garreth Hanley:
Great to have you on the show. First of all, let's just start with the basics. Can you explain what productivity means and the Australian Productivity Commission's approach, and how that fares in our modern economy?

Prof John Quiggin:
Sure. Well, the simplest version of productivity starts with, say, a single worker, say a shoemaker making shoes. The number of shoes the worker can make in a given number of hours is their productivity. And a related concept is crop yields on land. How much, say, wheat does a hectare of land yield? So those nice, simple measures. We have just took one number over the other. That ratio is productivity.

But the actual world of production is much more complicated than that. We produce a bunch of different things, and we require a bunch of different inputs to produce them. So we really need index numbers, an index which says we've added up the labour, capital, and other things that go into producing something. And we've also aggregated the output in some way so that we're aggregating across all the different things that a firm or an economy produces. And this index number ratio is what's called multi-factor productivity. So that gets much more complicated than simply how many shoes per hour does a shoemaker make, how many tonnes of wheat does a hectare produce.

So the Productivity Commission really started working hard on multi-factor productivity, along with the Bureau of Statistics, back in the 1990s. And at that time, they had a very good news story to tell, that we'd had a bunch of economic reform. And if you time things right, it seemed like we're getting this big acceleration in multi-factor productivity. That was the story in the 1990s. But that really was problematic at the time. And really, we've seen much weaker productivity growth ever since really the turn of this century.

In retrospect, part of the problem was, I think, that we weren't measuring labour correctly. This was a time of very rapid intensification of work. We just had a big recession. Everybody was being pushed to work harder and longer. And so we saw this increase in productivity coming out of that.

As the economy improved, people started being unwilling to do that, unwilling to do unpaid overtime and so forth. And so we haven't really seen that kind of strong productivity growth since the turn of the century. But the Productivity Commission is still very much of the view that what we need is more of the kind of reforms we had back in the 1980s that produced that initial surge in MFP.

Garreth Hanley:
Interesting. So what are those main findings from the Australian Productivity Commission's research?

Prof John Quiggin:
Well, as I say, our big finding is that we've seen this big slowdown in productivity, which wasn't expected. The reforms were still continuing right through the 1990s into the early 2000s. But that payoff on productivity didn't happen. And one thing which has more come out of the work of Commonwealth Treasury rather than the Productivity Commission is what we've been saved by is that computers have become cheaper and cheaper and more powerful.

We import those, of course. But the result is that even though, in some sense, our productivity hasn't grown, the importer part of our output has become massively cheaper. And so by using cheaper computers, we've been able to produce more, even though in a quantitative sense, it doesn't look like we're going anywhere.

Garreth Hanley:
Interesting. So it sounds like there's been a lot of technology change since that early measurement of MFP. How effective is MFP in today's world with all of that technology?

Prof John Quiggin:
Well, I think there are some big problems with all of the kind of measures we developed in the 20th century. So 20th century economy was one where essentially it was transforming raw materials into manufactured products, which were then sold, delivered to consumers or delivered as investment to keep the whole thing going. And when we had growth, that growth happened more or less across the board. And so the kind of productivity measures we have are really developed for that.

What we've seen certainly all this century, really probably starting right in the 1990s, is an economy that's incredibly uneven in the way in which we see growth and productivity. So the technology we're using right now to record this podcast has been entirely developed in the last 30 years and has become incredibly more powerful. The watch I'm wearing has more power probably than all the computers in the world at some time like 1980. And I can use it for the most trivial purposes or the most important.

On the other hand, if I get in my car, well, my car's quite old and the cars that are 20 years newer aren't really that much different. And so whereas we saw these big improvements in things like transport technology right through the 20th century, that's really pretty much ground to a halt, at least until we get our self-driving cars, which seems to be further off in the future. And so some parts of the economy have become massively more productive. Others really have not seen much productivity growth at all.

Garreth Hanley:
We've been talking about MFP, but there's also GDP, which is often used as an indicator for economic health and productivity. And I was just thinking about that example of us on this podcast. You're on one side of the country and I'm on the other, and we're doing this very cheaply. How does GDP fare in today's world?

Prof John Quiggin:
Well, again, badly. GDP is, well, for the purposes, as a summary index of welfare, not well at all. Again, GDP was really developed to deal with the problems of the 20th century industrial economy. So as I say, you did something like a farmer grew some wheat, a baker turned into bread, it was sent to a supermarket, and we bought it at the supermarket. Now, if you try and add all those things up, you get a nonsense number because the wheat in the flour, I forgot about the flour stage, that's counted again every time things go through a transaction, and we end up with a number which doesn't mean anything.

What GDP was designed to do was to look at the value added at each stage of production. And so when we looked at the productivity of a flour mill or the output of a flour mill, we deduct the value of the wheat that went into it. The flour would then be turned into bread. Again, we get the measures at each stage. And so we got a number which worked out what the economy was doing and measured the total level of activity.

That's why, for example, we use a gross number. Even though, in economic terms, we should be worrying about things like depreciation on the equipment in the factory, if we're trying to get an estimate of what's happening in the economy, which is what, for example, central banks are looking for, GDP is a useful number. But it's become less and less useful as a summary of how well off we are.

If we're somebody who doesn't care at all about computers and TV and electronics and really loves the products of the 20th century economy, things don't look great at all. Our wages really aren't keeping pace with things like the cost of health care and so forth. But if you like computers, this is the best possible time to be alive.

Garreth Hanley:
And you've mentioned some of these impacts of technology. But how is technology impacting these numbers, MFP and GDP numbers?

Prof John Quiggin:
Well, as I say, certainly making them less reliable as a guide to most things, except for the very narrow purpose of saying, is economic activity increasing or slowing? Now, that's what the Reserve Bank, for example, cares about when it decides on what to do about interest rates. If we see a big number for GDP growth in the last quarter or year, they think all things are hotting up. We might see some inflation resulting from that. Let's raise interest rates. If that number is low, that's something we may wish to cut interest rates.

But as a number for trying to work out, are people doing well, it's less and less useful.

Garreth Hanley:
John, recently we've had some discussions on the show about alternative measures of measuring well-being. Are there any other alternative measures for measuring productivity or emerging methods for measuring this?

Prof John Quiggin:
There are. I mean, I think in many ways the quest for a single number is just a mistake. As I've said, when you had the 20th century economy, everything was either getting better or occasionally getting worse at more or less the same pace. In the good years, most of the second half of the century, every year we had more of everything. When we had the Great Depression, we had pretty much less of everything.

But as that ceases to be true and as more of the economy depends on things like health and education, they're very hard to measure with a single number. I think this quest to find a single number to replace GDP, I think, is in many ways misconceived.

We need to be looking at a whole bunch of different things and trying to keep them in our head rather than worrying too much about single numbers.

Garreth Hanley:
So, every number has a blind spot?

Prof John Quiggin:
Well, yes. I mean, I think, and that's always been true to a certain extent. For example, one feature which I haven't mentioned so far, GDP was always about what happened out in the economy.

Now, in a very physical sense, of course, that's broken down with work from home, which is an important example.

But even before that, as the household became wired up, that division between the household and the economy has become less and less relevant. And I suppose it was precisely that process which made work from home possible. And that in turn means you really have to start paying attention to things like how much time do you spend travelling to work as part of your impact on work.

It makes any single number start to be less meaningful. If, for example, I am working at the university, there's some sort of fairly abstract measure of what's happened, really, actually only what I'm paid. So none of this stuff is measured really in GDP at all. Certainly the time that people have saved from commuting to work doesn't appear because commuting time never appeared in GDP in the first place.

Garreth Hanley:
Has there been impacts from work from home?

Prof John Quiggin:
Well, very clearly, you can talk to people and you can see that for workers who have access to it, it's seen as worth something like a 10% increase in wages. So there's this huge impact on how well off the people are who are benefiting from it. It's kind of unclear what effect it's had in terms of a measure of productivity for where it can be measured.

If you're, say, working in an insurance office, you can measure the claims per hour process or something like that. And it's unclear whether that's gone up or gone down. It might have slowed down a bit. And finally, there's been a hard to measure loss in welfare for people who really like being at the office and seeing other people at the office, which includes, among other things, most bosses.

So all of these things are hard to measure. And trying to get a handle on it through things like GDP hasn't proved very helpful.

Garreth Hanley:
Working from home has obviously been a big change, but it's not necessarily captured by GDP or MFP. Do we need something to capture the change that's happened? Because there has been a big change in society recently.

Prof John Quiggin:
Yes. Well, we certainly need an understanding of how much work from home is worth to workers. There's been some survey evidence, but that's very spotty. Some evidence, more evidence. To integrate evidence we have from things like time use survey, how much time has workers saved in commuting time? And then we need to look at questions where some people have suggested has output per hour on the job suffered? And is that more or less important than the savings?

The savings in things like commuting time, ability to multitask and so forth, that are the big benefits of work from home, but are sort of categorically excluded from numbers like GDP and MFP.

Garreth Hanley:
John, we always love to give people a few tips on our show. So how can businesses adapt their productivity strategies in light of our discussion and what we've been talking about today?

Prof John Quiggin:
Well, certainly work from home is an example where I think if you're only looking at the question of how much of your work is turning out per hour, you may be missing the fact that by allowing work from home, you're offering the equivalent of a substantially increase in wages.

So we've seen, of course, fairly weak wages growth. You need to consider if you're a manager seeking of a return to the office policy, whether there are going to be unmeasured costs and those costs will appear in things like worker retention and so forth.

Garreth Hanley:
That's really interesting. Thank you, John. It was really great to have you on the show today.

Prof John Quiggin:
Great to be here.

Garreth Hanley:
And thank you for listening to INTHEBLACK. Make sure to check out the show notes for links to the Australian Productivity Commission's research and other resources mentioned in today's episode.

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