Abstract
Aggregate book-to-market (B/M) ratio reflects market-wide assessments of growth opportunities and productivity. In this paper, I find that aggregate B/M innovations predict time-series variations in the U.S. economy. More importantly, the predictive content of the innovations is incremental (or even superior in a long-horizon forecast) to that of the Survey of Professional Forecasters (SPF). A real-time dating algorithm that is based on the innovations accurately identifies the business cycle turning points for the last 40 years. Decomposing aggregate B/M into components of accounting conservatism and delayed recognition of growth reveals different implications for the macroeconomic information content of aggregate B/M.
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