"Consumer Product Discovery Costs, Entry, Quality and Congestion in Online Markets"

(2020 - submitted)


(Online Appendix)


This paper examines the effects of changing consumer product discovery costs in online markets on entry and market congestion, as well as product design, quality and consumer welfare. Using new Android app store data, I take advantage of a natural experiment that reduces marginal discovery costs for game apps. I show that product entry increases, potentially increasing congestion. Average entrant quality falls. I disentangle the welfare effects of changing discovery costs and product assortment using a structural model of consumer demand and product entry that accounts for congestion externalities. I find that consumers' total welfare increases but two thirds of welfare gains from greater variety are lost due to higher congestion and lower entrant quality.

"The Effects of Influencer Advertising Disclosure Regulations: Evidence from Instagram" (2020)

with Matthew Mitchell


Extended Abstract published in ACM-EC 2020 Conference Proceedings (LINK)


We collect data from fifty top Instagram influencers in Germany and Spain from 2014 to 2019. Germany experienced changes in disclosure regulation for social media sponsorship during the sample period. Using a difference-in-difference approach, we study the impact of the the rules on the content of posts and the nature of interaction of followers with the posts. On the content side, we measure whether posts include suggested disclosure terms and show variable but substantial adoption of disclosure. We use an approach based on a fixed list of words associated with sponsorship (i.e. links, mentions of brands, use of words like "sale") as well as natural language processing to assess the likelihood that a post is sponsored. We show that sponsored content use may have increased after changes in disclosure and that followers may have been negatively affected. On the other hand, there is evidence that consumers’ reaction to sponsored posts, measured by likes, may be quite different under stricter disclosure rules, suggesting that the rules could have a substantial impact on information transmission.​

"Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market" (2020)

with Stephanie Assad, Robert Clark and Lei Xu

(draft available by request)


Economic theory provides ambiguous and conflicting predictions about the relationship between algorithmic pricing and competition. In this paper we provide the first empirical analysis of this relationship. We study Germany's retail gasoline market where algorithmic-pricing software became widely available by mid-2017, and for which we have access to comprehensive, high-frequency price data. Our analysis involves two steps. First we identify stations that adopt algorithmic-pricing software by testing for structural breaks in markers associated with algorithmic pricing. We find a large number of station-level structural breaks around the suspected time of large-scale adoption. Second, we investigate the impact of adoption on outcomes linked to competition. Since station-level adoption is endogenous, we instrument using brand headquarter-level adoption decisions. Our IV results show that adoption increases margins by 12%, but only in non-monopoly markets. Furthermore, restricting attention to duopoly markets, we find that market-level margins do not change when only one of the two stations adopts, but increase by nearly 30% in markets where both do. These results suggest that AI adoption has a significant effect on competition.

"Mergers in a Model with Complementarity" (2019)

with Mathieu Marcoux, Scott Orr and Jean-William P. Laliberté

(currently working on new version)


Standard discrete choice models used to evaluate mergers assume that different product varieties are substitutes. However, legal defences in some recent high-profile mergers rested on demand complementarity (e.g., GE/Honeywell). Since complements tend to be priced lower by a monopolist than by a duopoly, standard models will overstate consumer harm in these mergers. We use consumer level data from AC Nielsen look at two products with natural demand complementarities and a history of regulatory activity - potato chips and carbonated soda. We set up and estimate a discrete choice model that allows for demand complementarity and simulate a number of anti-trust counterfactuals in the chips and carbonated soda market. Once demand complementarity is taken into account, a merger between the chips/soda producer PepsiCo/Frito-Lay and the soda producer Dr. Pepper will reduce both chip and soda prices, on average. By contrast, the standard discrete choice model predicts that soda prices would always increase following the merger. An additional counterfactual breaking up the PepsiCo/Frito-Lay conglomerate suggests that both chip and soda prices will increase as a result.

"Competing with Superstars in the Mobile App Market" (2020 - submitted)


(NET Institute Working Paper 18-02)


Firms in many markets face substantial demand uncertainty in deciding where to enter new products. The appearance of a popular competitor (superstar) resolves part of this demand uncertainty or even expands demand. At the same time, a superstar intensifies competition. These two forces generate horizontal and vertical product differentiation tradeoffs for entrants: whether to enter near the superstar and whether to invest in quality. The effects of a superstar on market structure, quality and prices in the market are ambiguous in theory. I empirically examine these effects using Google Play Store mobile game data, taking advantage of the surprise emergence of superstar products for identification. I show that entry increases in niches where a superstar appears, unless these niches were previously popular. I also show that the appearance of superstars reduces the quality of new entrants and intensifies price competition. Incumbents respond to a superstar's appearance by investing in higher quality.

"Estimating the Effects of Deregulation in the Ontario Wine Retail Market" (2016)

with Victor Aguirregabiria and Junichi Suzuki



This paper studies the impact of competition in the Ontario wine market and evaluates the effects of alternative deregulation policies. The wine retail market of Ontario, Canada, is characterized by the coexistence of the government-owned Liquor Control Board of Ontario (LCBO) and two private companies. These private firms can sell only a limited subset of Ontario wines, and they are restricted on the number of stores they can operate. Our empirical results build on the estimation of a spatial demand model for differentiated products using a unique dataset from LCBO with information on store sales, prices, and product characteristics for every store and product in this retail chain over a two year period. Given the estimated demand model, we then simulate the effects of deregulation proposals (relative to a pure monopoly): (i) allowing for retail competition from the two privately-owned retail chains; (ii) removing the current restriction on selling non-Ontario wines by the two private wine retailers; and, (iii) allowing for price competition among the retailers. We show that compared to a pure monopoly market, the entry of additional competitors increases consumption and consumer welfare. By contrast, expanding the product range of existing competitors also increases consumer welfare, but keeps consumption stable


"Learned Complementarity"

with Adam N. Smith

"Do Consumers Prefer Local? Evidence from Ontario's Wine Industry"

with Jessica Burley and Michael Gilraine


“Market Incentives for Business Innovation: Results from Canada”

with Charles Bérubé and Marc Duhamel

Journal of Industry, Competition and Trade, Vol. 12(1), pp.47-65, 2012