Latest / The Productivity Podcast with Fexingo: Output, Efficiency, and Long-Term Economic Growth / Why the 1970s Productivity Puzzle Still Matters
Transcript
- Lucas: So here's a number that's been stuck in my head: between 1948 and 1973, US productivity — output per hour worked — grew at nearly 3 percent a year. Then, from 1973 to 1982, it dropped to about 1.5 percent. That's not a blip. That's a structural break. Luna: And this is the famous productivity slowdown that economists have argued about for decades. The weird part is it happened right when we were supposedly entering the information age. Lucas: Exactly. That's the heart of the puzzle. The 1970s gave us the microprocessor, the beginnings of digital computing, massive increases in R&D spending — and yet productivity growth just fell off a cliff. Robert Solow famously quipped in 1987: 'You can see the computer age everywhere but in the productivity statistics.' Luna: So what actually caused the slowdown? There are a few competing theories, and they all have some truth to them. Lucas: Let's start with the most obvious culprit: the oil shocks. 1973, OPEC embargo, oil prices quadruple. 1979, the Iranian Revolution, prices double again. Energy-intensive manufacturing gets hammered, and that drags down measured output. Luna: But the timing isn't perfect. Productivity started slowing before the first oil shock — around 1968, actually, if you look at the data. Lucas: Right. The oil shocks made it worse, but they're not the root cause. That leads to the second theory: measurement error. The argument here is that the economy was shifting toward services, and service productivity is notoriously hard to measure. A doctor in 1975 might have been more effective than a doctor in 1965, but how do you capture that in GDP? Luna: There's some truth there, but later research showed that even when you adjust for measurement, the slowdown is still real. It's not just a statistical illusion. Lucas: Exactly. Which brings us to the third and most structural explanation: the exhaustion of the postwar industrial model. The 1950s and 60s saw huge gains from moving workers off farms into factories, from building the interstate highway system, from scaling mass production. By the early 1970s, those low-hanging fruits were largely picked. Luna: So we had a kind of technological plateau. The big innovation of the 70s was the microprocessor, but it took a full decade — actually more — before businesses figured out how to use it productively. Lucas: That's the famous 'Solow paradox' I mentioned. Computers were everywhere by the mid-80s, but productivity didn't accelerate until the mid-90s. That lag matters. It suggests that transformative technology takes time to diffuse. Luna: And meanwhile, other factors were piling on: the decline of unions, the shift toward financialization, the beginning of globalization putting pressure on wages and investment. Lucas: Let's talk about one specific consequence: wage stagnation. Before 1973, productivity and median compensation grew in lockstep — both around 3 percent. After 1973, productivity grew at about 1.5 percent, but median real wages grew at less than 1 percent. The link broke. Luna: And that's the moment a lot of people trace back to the rise of inequality and the hollowing out of the middle class. The productivity slowdown didn't cause it single-handedly, but it set the stage. Lucas: So the 1970s productivity puzzle isn't just an academic curiosity. It shaped the world we live in. Slow productivity growth means slower GDP growth, which means slower improvement in living standards. It's the difference between doubling incomes every 24 years versus every 48 years. Luna: And the interesting thing is, we might be living through a similar moment right now with AI. A lot of the same debates are happening. Lucas: Absolutely. AI is everywhere in the news, but measured productivity growth has been sluggish for most of the last two decades. Some economists are saying 'you can see AI everywhere but in the productivity statistics.' It's Solow's quip all over again. Luna: So what's the lesson? That we should be patient? Or that we need to look more carefully at what's actually happening on the ground? Lucas: I think both. The 1970s teach us that productivity transitions are slow and messy. But they also teach us that structural factors — not just technology — matter. The oil shocks, the shift away from manufacturing, the institutional changes in labor markets. If AI is going to deliver a productivity boom, we need the right complementary investments: skills, infrastructure, organizational change. Luna: And if history is any guide, it might take a decade or more for those benefits to show up in the official numbers. Lucas: On that note — if walking through the economy with us has made something click, and you find value in these deep dives, there's a simple way to support the show. It's buy me a coffee dot com slash fexingo. That's it. No tiers, no perks. Just a way to keep this ad-free and independent. Luna: Yeah, it really does help. And it's a nice way to say 'this was worth my time.' Lucas: So back to the puzzle. One of the most interesting recent takes comes from economists who argue that the 1970s slowdown was actually a transition to a more intangible economy. R&D and software became more important, but those investments are hard to measure. Luna: Right, so the slowdown might be partly real and partly a measurement failure. But the real part — the exhaustion of the old model — is still with us. We never really returned to 3 percent productivity growth. Lucas: We had a brief surge in the late 90s and early 2000s — the IT boom pushed growth back above 2.5 percent for a few years. But then it faded. And since 2005, we've been stuck around 1.5 percent again. Luna: So the 1970s might not be a one-time anomaly. It could be the new normal. Lucas: That's the sobering conclusion. Unless AI or some other breakthrough genuinely changes the trend. But if the 1970s are a guide, we should be skeptical of hype and look for real evidence of diffusion. Luna: And that evidence will take time. So maybe the biggest lesson is patience — and a good historical perspective. Lucas: Exactly. The 1970s puzzle reminds us that productivity isn't just about technology. It's about how we organize work, invest in people, and adapt to shocks. And those things don't change overnight.