Episode 360: Robert J. Gordon

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Measuring Labor Productivity

How do you measure the true productivity of a country’s economy? What gets missed if the only metric being examined is the GDP? 

Robert J. Gordon is a professor of social sciences and economics at Northwestern University. His work focuses on the history of labor and capital productivity and has written numerous books, including, The Rise and Fall of American Growth: The U.S. Standard of Living since the Civil War

Robert and Greg discuss why the GDP doesn’t give a full picture of a country’s economic growth and productivity, why the years between 1929 and 1950 saw the most rapid growth, and whether or not we’ll see another growth spurt in the age of AI. 

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Episode Quotes:

Is our productivity running low?

37:46:  If we compare the forecasts of productivity growth that are baked into the government's budget forecasts and economic forecasts, our productivity over the last nearly 20 years has been running somewhat slower than they're assuming for the future. So, there's room for productivity growth to improve by a substantial amount without really changing the overall outlook for this enormous increase in public debt. That is going to go together with higher interest rates and severely impede the ability of future governments to finance Medicare, Social Security, and the general operations of government.

Understanding the US productivity growth

09:39: The fact is that the economy was producing well under its capacity in the 1930s, and it's a black box to figure out how much the economy was capable of. But we were producing at full capacity in 1929, and we certainly were in 1948, and so the growth rate between those two years was by far the most rapid that we have had.

On measuring total factor productivity

09:19: One of the fuzzy dividing lines in measuring total factor productivity is how much of the innovation is attributed to the capital and treated as an increase in the quantity of the capital, thus diminishing that ratio I just expressed. And how much of it comes out as the difference between output and input growth, and that dividing line is somewhat the quality of capital.

ChatGPT and the potential job losses for future productivity gains

32:34: To interpret ChatGPT and the potential for job losses for future productivity gains, it helps to break down the economy into three groups of workers. One group produces goods in mines, in farms, in factories, and they're producing objects with other objects. They're not involved in creating textual or visual material. So, the impact in the goods sector is going to be fairly minor, certainly compared to the development of automation. 

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