From my new paper with Ben Southwood on whether the rate of progress in science is diminishing:
Similarly, the tech sector of the American economy still isn’t as big as many people think. The productivity gap has meant that measured GDP is about fifteen percent lower than it would have been under earlier rates of productivity growth. But if you look say about the tech sector in 2004, it is only about 7.7 percent of GDP (since the productivity slowdown is ongoing, picking a more recent and larger number is not actually appropriate here). A mismeasurement of that tech sector just doesn’t seem nearly large enough to fill in for the productivity gap. You might argue in response that “today the whole economy is incorporating tech,” but that doesn’t seem to work either. For one thing, recent tech incorporations typically involve goods and services that are counted in GDP. Furthermore, there is a problem of timing, namely that the U.S. productivity slowdown dates back to 1973, and that is perhaps the single biggest problem for trying to attribute this gap mainly to under-measured innovations in the tech sector.
Other research looks at “worst case” scenarios from the mismeasurement of welfare adjustments in consumer price deflators and finds a similar result: a significant effect that nonetheless does not reverse the judgement that innovation has been slowing.
The most general point of relevance here is simply that price deflator bias has been with productivity statistics since the beginning, and if anything the ability of those numbers to adjust for quality improvements may have increased with time. For instance, the research papers do not find that the mismeasurement has risen in the relevant period. You might think the introduction of the internet is still undervalued in measured GDP, but arguably the introduction of penicillin earlier in the 20th century was undervalued further yet. The market prices for those doses of penicillin probably did not reflect the value of the very large number of lives saved. So when we are comparing whether rates of progress have slowed down over time, and if we wish to salvage the performance of more recent times, we still need an argument that quality mismeasurement has increased over time. So far that case has not been made, and if you believe that the general science of statistics has made some advances, the opposite is more likely to be true, namely that mismeasurement biases are narrowing to some extent.
You will find citations and footnotes in the original. Here is my first post on whether the productivity gains from the internet are understated.