Research
I study the economics of data and its implications for platform strategy and regulation.
Job Market Paper
Opening the Black Box: A Statistical Theory of the Value of Data
Abstract
This paper develops a theory of the value of data for prediction. An agent chooses a sample of individuals and a subset of their covariates to collect in order to estimate the parameters of a data-generating process and predict an outcome for a representative individual based on her covariates. The main findings are: (i) covariates collected on the sample exhibit economies of scope, as the value of collecting a covariate on the sample increases when another is observed; (ii) the value of collecting a covariate on the sample is inverted-U-shaped in the sample size; and (iii) the value of collecting a covariate on the representative individual is strictly increasing in the sample size. These patterns have several policy implications. First, firms that collect different covariates and sell predictions in separate markets may find it profitable to merge even when this reduces welfare, particularly when data are scarce due to, for example, privacy regulation. Second, agreements that allow firms to sell covariate bundles are always procompetitive because they eliminate double marginalization, whereas bundling observations can be anticompetitive when data are abundant because it raises the price of data. Third, when selling data to competing prediction providers, a data seller may profitably exclude one buyer even though this reduces total welfare, especially when competition among providers is fierce and data are abundant.
Working Papers
The Price of Stability: the Rise in Markups and the Great Moderation
Abstract
During the Great Moderation, macroeconomic volatility declined while firm markups increased. We document a causal relationship between volatility and markups due to tacit collusion. We exploit the legalisation of interstate banking as an exogenous decrease in volatility. Using an instrumental variable approach, we show that a 1% reduction in volatility causes a 19 p.p. increase in aggregate markups. The effect is due to large firms and firms operating in non-tradable industries. The changing market structure explains two-thirds of the effect, whereas reallocation only accounts for one-third. The reduction of volatility during the Great Moderation explains 31% of the markup increase between 1980 and 1997.
Data Combination and the Supply of Privacy-Protecting Apps
Abstract
The paper analyzes the interplay of positive data spillovers across apps and negative privacy externalities across app users. We show that these two forces affect social welfare of the market equilibrium in opposite directions, potentially leading to suboptimal business model choice on part of ad-funded apps which share data through an ad tech platform. We apply the model to analyze Apple Ad Tracking Transparency and the Digital Markets Acts provisions on user consent on tracking to show that these initiatives can increase social welfare.