Digitization, Prediction, and Market Efficiency: Evidence from Book Publishing Deals

Abstract

Digitization has given creators direct access to consumers as well as a plethora of new data for suppliers of new products to draw on. We study how this affects market efficiency in the context of book publishing. Using data on about 50,000 license deals over more than 10 years, we identify the effects of digitization from quasi-experimental variation across book types. Consistent with digitization generating additional information for predicting product appeal, we show that the size of license payments more accurately reflects a product’s ex post success, and more so for publishers that invest more in data analytics. These effects cannot be fully explained by changes in bargaining power or in demand. We estimate that efficiency gains are worth between 10% and 18% of publishers’ total investments in book deals. Thus, digitization can have large impacts on the allocation of resources across products of varying qualities in markets in which product appeal has traditionally been difficult to predict ex ante. This paper was accepted by Joshua Gans, business strategy.