a larger share of u. s. gross domestic product - 5 ( gdp ), the category has only one single dedicated quarterly report, even though much of the post - pandemic recovery requires us to understand how services consumption and employment have evolved. for example, did you know that quarterly hog and pig counts are a principal economic indicator? yet, there is not a regular government report specifically dedicated to the gig economy. i am certainly glad we collect data for important agricultural commodities, but i think we should probably be examining the large and diverse gig economy as much as we do the pig economy. i believe the statistical agencies grapple with these issues, and it takes time to lay the groundwork and develop new data series, but this challenge is a real one. if reports are built for the past, that may mean they struggle to capture big developments today and in the future, such as the changing nature of where and how people work or the rising use of artificial intelligence ( ai ) technology. finally, there is an impediment that everyone here is acutely aware of : these challenges are made even more difficult because official surveys have seen declining survey response rates. that results in lower precision of statistical estimates and can lead to the need for further, costly surveys to collect the necessary amount of information, as one may need to conduct several rounds of data collection before having sufficiently large samples that can provide reliable estimates. declining response rates may also be selective and pose a challenge to representing the broader population. innovative methods for data collection and behavioral interventions to encourage survey responses can be used to address concerns and are being tried in some cases by statistical agencies. - 6a data explosion while these challenges in traditional data that i have described may take some time to be addressed, i am encouraged by the explosion in data produced by the private sector over the past decade or so that can greatly enhance our understanding of the economy. such data give an opportunity to measure economic developments with greater timeliness, at a higher frequency, and with more granularity. that said, those data often face their own challenges, including issues with representativeness, the lack of methodological consistency, and a short time - series history. nevertheless, such nontraditional data can be helpful, especially when used jointly with official statistics to which these new sources can be benchmarked. a prominent example of valuable private - sector data is employment statistics from payroll providers. such weekly data allowed economists at the federal reserve board to understand, essentially in real

new technologies. the development of electric utilities was another important source of productivity gains in the 1920s. expansion and consolidation considerably boosted efficiencies in the industry during that decade, although signs of excess capacity were not evident. on the other hand, share prices of these firms soared, with a stunning run - up late in the decade. share prices collapsed in the great depression, but again did not return to the pre - depression peaks until the mid - 1960s, suggesting again the possibility that a bubble had developed in the earlier period. finally, we consider the airline industry. after lindbergh's 1927 transatlantic flight, airline stocks soared, and many companies rushed into the business. stock in a company called seaboard air lines took off even though it was just a railway company, a phenomenon analogous to that of adding a dot - com suffix to company names in the late 1990s. interestingly, none of our examples overlaps with the golden age. that period seems to be characterized by a broader range of smaller innovations and perhaps, therefore, did not appear to give rise to the same frenzy of investment activity or euphoria with respect to valuations. in the examples above, innovations generally resulted in investment booms in the innovating sector but not always in the broader economy. the innovations often seemed to result in bubbles in valuations in the innovating sector, but this did not necessarily dominate the equity valuations for the entire economy. after a period, the innovating sector often experienced a shakeout or retrenchment, though that didn't always dominate the macrodynamics of the entire economy. nevertheless, in the examples in which booms were followed by retrenchments, the sector in question made important contributions to productivity long after the shakeout. these historical examples draw heavily from frank and browning ( 2001 ), gould ( 1946 ), wessel ( 2001 ), and white ( 1990 ). see white ( 1990 ). iii. sustainability and the new economy let me now return to the present day and turn to the task of understanding the sharp slowdown under way and the particular features of recent experience that seem so central to understanding the forces at work. i refer here to the correction in equity prices and the retrenchment of investment, both of which are centered on the high - tech area. as we begin to ask the question, what happened to the new economy, many of you, i expect, may believe that the answer stands right