"Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market" (2021)
with Stephanie Assad, Robert Clark and Lei Xu
We provide the first empirical analysis of the relationship between algorithmic pricing (AP) and competition by studying the impact of adoption in Germany's retail gasoline market, where software became widely available in 2017. Because adoption dates are unknown, we identify adopting stations by testing for structural breaks in AP markers, finding most breaks to be around the time of widespread AP introduction. Because station adoption is endogenous, we instrument using headquarters adoption. Adoption increases margins, but only for non-monopoly stations. In duopoly stations, margins increase only if both stations adopt, suggesting that AP has a significant effect on competition.
"The Effects of Advertising Disclosure Regulations on Social Media: Evidence From Instagram" (2021)
with Matthew Mitchell
Extended Abstract published in ACM-EC 2020 Conference Proceedings (ABSTRACT, 2020 ACM-EC FULL)
We study the effects of advertising disclosure regulations in social media markets. Theory generates ambiguous predictions about the effects of regulations on the equilibrium amount of advertising content, user engagement and welfare. Using data from a large sample of Instagram influencers in Germany and Spain and a difference-in-differences approach, we empirically evaluate the effects of German disclosure regulations on post content and follower engagement. We measure whether posts include suggested disclosure terms and use text-based approaches (keywords, machine learning) to assess whether a post is sponsored. We show a substantial adoption of disclosure after regulations, but also an increase in sponsored content including undisclosed sponsored content. We also find reductions in engagement, suggesting that followers were likely negatively affected.
"Estimating Complementarity with Large Choice Sets: An Application to Mergers" (2021)
with Mathieu Marcoux, Scott Orr and Jean-William P. Laliberté
Standard discrete choice models assume that products are substitutes. Merger analyses based on these models may overstate consumer harm when producers of complementary products merge. Allowing for demand complementarity greatly complicates demand estimation, particularly when the number of choices is large. We introduce a straightforward Generalized Method of Moments estimator that identifies preferences allowing for (1) potential consumption complementarity, (2) price endogeneity and (3) large choice sets. Our estimator parsimoniously leverages information on consumer level bundle specific purchases and aggregate sales data. We apply this estimator to the chips and soda market and find a high degree of complementarity between these product groups. We show that a merger between PepsiCo/Frito-Lay and Dr. Pepper would increase soda prices by 30% less than suggested by a model that does not account for complementarity. Post-merger chip prices decrease. Overall, accounting for complementarity leads to positive welfare gains in some markets with large numbers of Frito-Lay varieties.
"Consumer Product Discovery Costs, Entry, Quality and Congestion in Online Markets"
(September 2020 -R&R AEJ:Micro)
This paper examines the effects of changing consumer product discovery costs in online markets on entry, market congestion, quality and consumer welfare. Using new Android app store data, I take advantage of a natural experiment that reduces discovery costs for game apps. I show that entry increases when discovery costs fall, potentially increasing congestion. Entrant quality falls. I disentangle the welfare effects of changing discovery costs and product assortment using a structural model that accounts for congestion externalities. I find that consumers' welfare increases but fifty percent of variety welfare gains are lost from higher congestion and lower entrant quality.
"Sharing News Left and Right: The Effects of Policies Targeting Misinformation on Social Media" (2021)
with Juan S. Morales
We study Facebook's and Twitter's policy interventions which aimed to reduce the spread of misinformation during the 2020 US election. Facebook changed its news feed algorithm to reduce the visibility of content, while Twitter changed its user interface, nudging users to be more thoughtful about sharing content. Using data on tweets and Facebook posts published by news media outlets, we show both policies significantly reduced news sharing, but the reductions varied heterogeneously by outlets' factualness and political slant. On Facebook, content sharing fell relatively more for low-factualness outlets. On Twitter, content sharing fell relatively more for left-wing and high-factualness outlets.
"Competing with Superstars in the Mobile App Market" (2020)
(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
WORK IN PROGRESS:
with Adam N. Smith
"Do Consumers Prefer Local? Evidence from Ontario's Wine Industry"
with Jessica Burley and Michael Gilraine
"Autonomous Algorithmic Collusion: Economic Research and Policy Implications"
with Stephanie Assad, Emilio Calvano, Giacomo Calzolari,
Robert Clark, Vincenzo Denicolò, Justin Johnson, Sergio Pastorello,
Andre Rhodes, Lei Xu and Matthijs Wildenbeest
Oxford Review of Economic Policy, forthcoming
“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