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"We analyze the equilibrium size of the active management industry and the role of historical data--how investors use it to decide how much to invest in the industry, and how researchers use it to judge whether the industry's size is reasonable. As the industry's size increases, every manager's ability to outperform passive benchmarks declines, to an unknown degree. We find that researchers need not be puzzled by the industry's substantial size despite the industry's negative track record. We also find investors face endogeneity that limits their learning about returns to scale and allows prolonged departures of the industry's size from its optimal level"--National Bureau of Economic Research web site

We develop a general equilibrium model in which stock prices of innovative firms exhibit "bubbles" during technological revolutions. In the model, the average productivity of a new technology is uncertain and subject to learning. During technological revolutions, the nature of this uncertainty changes from idiosyncratic to systematic. The resulting bubbles in stock prices are observable ex post but unpredictable ex ante, and they are most pronounced for technologies characterized by high uncertainty and fast adoption. We find empirical support for the model's predictions in 1830–1861 and 1992–2005 when the railroad and Internet technologies spread in the United States. (JEL G12, L86, L92, N21, N22, N71, N72)