We find that mismeasurement error has biased construction-sector productivity growth downward by 3⁄4pp per year at the very most. This brings an estimate of average productivity growth from 1987 to 2019 up to positive territory, but just barely (from negative 0.5% to positive 0.2%), and still about 1pp below productivity growth of the next-lowest major industries and more than 11⁄2pp below the average for the nonfarm business sector. Consequently, we conclude that productivity growth may well have been quite low in the construction industry, even if it has not been as low as implied by the official statistics. While this estimated growth rate is higher than the growth rate of the published data, it does not change the qualitative result that productivity growth in this sector has been quite low. And our estimate of productivity growth in the construction sector remains much lower than in other industries. Related: The Strange and Awful Path of Productivity in the U.S. Construction Sector and Construction Industry Has Work, Needs More Workers
- Date Posted:
- August 7, 2023
If you are using equity risk premiums or even earnings yield for market timing, recognize that having a high R-squared or correlation in past returns will not easily translate into market-timing profits, for two reasons. First, the past is not always prologue, and market and economic structures can shift, undercutting a key basis for using historical data to make predictions. Second, even if the correlations and regressions hold, you may still find it hard to profit from them, since you (and your clients, if you are a portfolio manager) may be bankrupt, before your predictions play out. Statistical noise (the standard errors on your regression predictions) can create havoc in your portfolios, even if it eventually gets averaged out.