Abstract

The digital advertising industry is characterized by a proliferation of specialized intermediaries helping advertisers in their purchases of online ad space. This study contributes to the analysis of the vertical complementarities in this market by posing and estimating a structural econometric model of how advertisers match to intermediaries. Exploiting novel data and some recent methods in the estimation of many-to-many matching games for large markets, we quantify the value created by the matches, their driving forces and, counterfactually, evaluate the likely effects of the growing concentration among intermediaries. The estimates clearly show that competing advertisers benefit from dealing with a common intermediary and, moreover, offer a precise quantification of various forces including industry specialization, exclusive contracting and diversification.

Abstract

Maintaining good ratings increases the profits of sellers on online platforms. We analyze the role of strategic pricing for ratings management in a setting where a monopolist sells a good of unknown quality. Higher prices reduce the value for money, which on average worsens reviews. However, higher prices also induce only those consumers with a strong taste for the product to purchase, which on average improves reviews. Our model flexibly parametrizes the two effects. This parametrization can rationalize the observed heterogeneity in the relationship between reviews and prices and highlights the dependence of outcomes on the dominant effect. We analytically characterize a seller’s optimal dynamic pricing strategy, long-run profits and consumer surplus, as well as consumers’ speed of learning. Knowledge of the relative strength of price and selection effect is essential for managing ratings with prices. Our results have important implications for the design of rating systems.

Abstract

Online reviews significantly impact consumers' decision-making process and firms' economic outcomes and are widely seen as crucial to the success of online markets. Firms, therefore, have a strong incentive to manipulate ratings using fake reviews. This presents a problem that academic researchers have tried to solve over two decades and on which platforms expend a large amount of resources. Nevertheless, the prevalence of fake reviews is arguably higher than ever. To combat this, we collect a dataset of reviews for thousands of Amazon products and develop a general and highly accurate method for detecting fake reviews. A unique difference between previous datasets and ours is that we directly observe which sellers buy fake reviews. Thus, while prior research has trained models using lab-generated reviews or proxies for fake reviews, we are able to train a model using actual fake reviews. We show that products that buy fake reviews are highly clustered in the product-reviewer network. Therefore, features constructed from this network are highly predictive of which products buy fake reviews. We show that our network-based approach is also successful at detecting fake reviews even without ground truth data, as unsupervised clustering methods can accurately identify fake review buyers by identifying clusters of products that are closely connected in the network. While text or metadata can be manipulated to evade detection, network-based features are more costly to manipulate because these features result directly from the inherent limitations of buying reviews from online review marketplaces, making our detection approach more robust to manipulation.

Abstract

We conduct a large-scale online experiment, where we compare the short- and longer-term effects of fact checking to a brief media literacy intervention (ten tips to spot false information) as a means to debunk “fake news". We find that the effect of fact checking is limited to the specific “fake news" that are being targeted, whereas the media literacy intervention helps users to distinguish between false and correct information more generally, both immediately and two weeks after the intervention. Our results promote media literacy as an effective tool against “fake news", that is furthermore cheap, scalable, and easy-to-implement by social media platforms.

Abstract

We consider a merger between firms that operate on data-connected markets: products are neither substitutes nor complements, but  sales on market A generate data that can be potentially used on market B. We show that the effects of the merger depend on (i) whether data is pro- or anti-competitive on market B, (ii) the existence of frictions regarding the trade of data, (iii) the intensity of competition on market A. 

Abstract

In this paper, we build a model of the news market where advertisers choose to allocate their ads between a social media platform and a news website that is the content creator. Our main objective is to evaluate a policy intervention that aims to foster news creation by redistributing revenues from social media to news websites. Such interventions, commonly referred to as news media bargaining codes, were first implemented in Australia in 2021 and have been recently debated worldwide. We focus on a novel trade-off between the higher advertising efficiency of social media and the value of content creation by news websites.  We find that a parameter region always exists where the equilibrium level of news creation is socially sub-optimal. Moreover, we show that policy intervention mandated by the bargaining code is always welfare-increasing. We identify conditions when the policy even results in a Pareto improvement over laissez-faire. We show that in all other cases, the improved welfare comes at the detriment of the social media company. The main results hold under different news consumption behaviors and ad pricing mechanisms. 

Abstract

We explore the impact of a feature on a large review platform that allows users to more easily observe the ethnicity of black-owned restaurants. We find that the addition of this feature increased demand for black owned businesses. The results suggest that the effect is larger in areas that are higher income, higher education, and in areas that are predominantly white.

Abstract

This paper analyzes the impact of the recent trade tensions between the United States of America and China on the prices of smartphones commercialized in uninvolved countries. The empirical analysis relies on a large dataset of daily prices of smartphones commercialized in Austria, France, Germany, Italy, Spain, and the United Kingdom. The events related to the ongoing trade war offer a natural experiment that can be used to test the causal relationship between trade tensions and the price development of smartphones. The estimation results suggest that the ban on Huawei’s products in the U.S. impacted negatively and significantly the prices of the smartphones sold by the Chinese firm in all of the countries studied. Also, I find that both Huawei and Android increased their market shares in the focal countries. This paper is the first to provide empirical evidence of the consequences of the ongoing trade war on the prices of durable goods in uninvolved countries.

Abstract

Recent literature has shown that the existence of supply and demand-side non-generic complementarities (“demand-side linkages") within ecosystems raises questions about the pertinence of defining a single relevant market comprising substitute products (“substitutability approach"). However, empirical methodologies to measure these linkages and asses the competitive dynamics underpinning them are lacking. Using recent data from internet traffic between the major 246 European digital platforms, we develop such a methodology and test some theoretical findings of the ecosystems literature with major implications for competition and regulatory analysis. We corroborate that demand-side linkages are a non-negligible phenomenon: 18% of these platforms show them. However, unlike what the ecosystems literature predicts, in roughly half of the cases they do not link complementors but platforms competing in at least one market. Finally, while, as expected, we observe demand-side linkages mostly within industry-defined ecosystems, we find evidence of industry-agnostic ecosystems. These could be instigated and orchestrated by platform users instead of by a firm. We conclude that the substitutability approach is not obsolete, but needs to be complemented with alternative approaches in order to i) take into account coopetition within the same relevant market and ii) analyze how the competitive process in one market can impact the welfare generated in another (industry's) market through non-generic complementarities.

Paper available here.