Are Markups Too High? Competition, Strategic Innovation, and Industry Dynamics
with Laurent Cavenaile and Xu Tian
Revise and Resubmit at the Review of Economic Studies
Abstract: To study competition, innovation, and industry dynamics that arise as a result of their interaction, we develop a new oligopolistic general-equilibrium Schumpeterian growth model. This model ties together the endogenous growth, oligopolistic competition, and dynamic industrial organization literatures in a single unified framework, which is used to assess the growth and welfare implications of counterfactuals. Within each industry, there are an endogenously determined number of large firms (“superstars”) that compete a la Cournot and a continuum of small firms which collectively constitute a competitive fringe. Firms dynamically choose their innovation strategies, cognizant of other firms’ choices, and their entry and exit are endogenous. The model is consistent with the macroeconomic trends observed in the United States since the 1970s, such as the domination of industries by a small number of superstar firms, the rise of markups, market concentration, profits, and R&D spending, and the decline in business dynamism, productivity growth, and the labor share. It replicates the empirical relationship between innovation and competition within and across industries. As an application, we estimate the model to disentangle the effects of separate mechanisms on the structural transition observed in the United States, which yields striking results: (1) While the increase in the average markup causes a significant static welfare loss, this loss is overshadowed by the dynamic welfare gains from increased innovation in response to higher profit opportunities. (2) The increasing costs of innovation are found to be the primary determinant of lackluster productivity growth, i.e., ideas are getting harder to find.
A Theory of Dynamic Product Awareness and Targeted Advertising
with Laurent Cavenaile, Jesse Perla, and Pau Roldan-Blanco
Revise and Resubmit at the Journal of Political Economy
Previously called: “A Model of Product Awareness and Industry Life Cycles.”
Abstract: Rapid technological advances in advertising have enabled firms to better target those consumers most likely to buy their products. While more efficient than traditional methods, targeted advertising may significantly limit product market competition. We develop a novel framework of demand as a network, where heterogeneous consumers dynamically become “aware” of differentiated products, expanding their choice sets and improving on their possible matches thanks to advertising. As networks become denser, customer misallocation decreases due to better sorting. However, though more intensive targeting can efficiently sort with fewer network connections, it also increases market power by segmenting consumers. Despite the rich micro structure, we show that the model aggregates to a neoclassical growth economy with endogenous TFP. As an application, we consider the case of the United States over a period of time which saw a rapid rise in digital advertising. We find that this rise led to substantially better consumer-firm matches. However, if the targeting technology had not improved during this period, markups would have been lower and welfare higher despite worse sorting.
Identifying the Heterogeneous Impact of Highly Anticipated Events: Evidence from the Tax Cuts and Jobs Act
with Paul Borochin, Xu Tian, and Toni Whited
Abstract: We develop a method for estimating individual firm heterogeneity in the stock market impact of aggregate events, using data on both stock and options prices. Our method impounds the effects of event anticipation. We apply the method to the passage of the Tax Cuts and Jobs Act (TCJA), which exhibits both anticipation and heterogeneity. We estimate that the market anticipated the probability of passage to be 95% 30 days before the event. The full value impact of the TCJA is 12.36%, compared to 0.68% when market anticipation is ignored. Large, innovative firms with high growth prospects are the largest winners.
The Efficiency of Patent Litigation
with Samuel B. Antill, Xu Tian, and Toni Whited
Abstract: How efficient is the U.S. patent litigation system? We quantify the extent to which the litigation system shapes innovation using a novel dynamic model, in which heterogeneous firms innovate and face potential patent lawsuits. We show that the impact of a litigation reform depends on how heterogeneous firms endogenously select into lawsuits. Calibrating the model, we find that weakening plaintiff rights through fewer defendant injunctions increases firm innovation and output growth, improving social welfare. Raising plaintiff pleading requirements, which heightens barriers to filing lawsuits, likewise promotes innovation, boosts output growth, and enhances social welfare.
Patents as Collateral and Directed Technical Change
with Ufuk Akcigit, Olga Itenberg, and Guillermo Ordonez
Abstract: In recent years, and in spite of their intangible nature, patents have been increasingly used as collateral. We show that this financial innovation has disproportionately drawn firm entry into more crowded innovative industries, those where patents are easier to trade. We study the effects of the use of patents as collateral in a multi-sector endogenous growth framework with expanding input varieties, where the intermediate sectors differ in market size. Our model predicts that the use of patents as collateral directs future technological progress towards sectors with more patenting firms, which are not necessarily the most productive sectors. Even though the use of patents as collateral relaxes financial frictions, they also have the potential to direct technological innovation inefficiently, which we explore quantitatively.