Market Outcomes and Regulatory Response

The work program of the research group is divided into three areas. "Consumer Behavior and Firms' Response" is one of them. Each area is divided into three projects. This area's projects are:

P7: Consumer Behavior and Search on Platforms

Consumer search behavior and reactions of firms to this behavior is a very important topic that drives efficiency of markets. This holds particularly for online platforms, as they have considerably facilitated consumer search in recent years. A platform might have an incentive to steer consumers to search results in its preferred way, as it collects commissions over sales. However, those incentives are not necessarily aligned with the ones of consumers, which may call for consumer protection and regulatory interventions (see the EC’s Digital Markets Act, 2020, and the US bills, 2021). In this project, we aim at developing a platform model that explicitly takes into account the platform’s gatekeeper role of providing access to information about products to consumers and the consumers’ search behavior. We plan to analyze different instruments to steer consumers with respect to their competitive consequences. Among these instruments are different ranks in the listing, default settings for searches, and salience of paid-for-advertisements. We explicitly consider how consumers’ choice sets are determined by the search rule of a platform, that consumers have a limited amount of time to search or face behavioral biases by forming incorrect reference points. All these can potentially be exploited by platforms. We plan to consider in detail how consumers’ beliefs about a platform’s ranking mechanism affect consumers’ search for their best match and the equilibrium behavior of platforms. We want to develop a search model that allows for flexible consumer behavior and includes either knowledge or ignorance of commission fees. Our goal is to provide a framework, which allows us to derive potential welfare consequences of distorted consumer beliefs about ranking criteria and assess different policy tools with respect to their effectiveness in reducing distortions of welfare in the market of ranking websites. This will also help us to understand better whether competition can mitigate or may even exacerbate potential inefficiencies and how multi-homing consumers may adjust their beliefs. This is an important step to gain knowledge how transparent information about ranking criteria changes consumer search. We also plan an analysis of the filtering choices of platforms on comparison websites. Prominence of filtering attributes induces consumers to put more emphasis on these attributes when comparing products, which may facilitate search. However, consumers need to spend time and effort to discover potentially important attributes of these products that are not listed in the filters. The filtering choices are again driven by consumer beliefs on how platforms choose their respective filters and rankings, dependent on factors consumers focus on when comparing listings. We would like to build a general consumer search framework to analyze how filtering attributes affect consumers’ search and the platform’s optimal choice of these attributes.

P8: Structuring Financial Products to Exploit Retail Investors with Limited Attention

Building on experimental as well as observational field data this project seeks to determine the implications of retail investors’ limited attention for investment choices and firms’ design of financial products. In this project we are interested in those salience effects that financial firms can (easily) exploit, namely effects related to the labelling of financial products, the relative positioning of financial products and the marketed investment strategies for financial products. There is much suggestive evidence that such exploitation is going on. For instance, the number and variety of stock market indices has increased rapidly. For the last five years, there are more investable indices in the US than listed firms, while on average only five funds use a given index and 75 percent of indices are adopted by a single fund. Such niche indices charge higher fees than broadly adopted benchmarks, and just three firms capture 80 percent of the market for benchmark index provision in 2018. While classical economic models have a hard time explaining these patterns, insights from the literature on limited attention can. Learning about the precise channel that drives such patterns is particularly important to draw suitable policy implications. Precisely, we would like to understand experimentally (1) how benchmarks can be chosen to make products look more favorable and thereby increase firms’ profit margins, and (2) which investment strategies firms can prominently advertise in order to increase investments. By means of experiments and structural models, we want to test (3) how attention-grabbing labels can be used to direct demand toward financial products that are dominated in terms of their cost structure. Finally, structural models should provide insights on (4) how policies that restrict the availability of niche benchmarks and extend the consideration set of retail investors affect investor welfare and the profits of index providers and funds.

P9: Consumer Inertia and Regulatory Responses

The overarching objective of this project is to better understand how consumer inertia affects firms’ strategies, market outcomes, and the suitability of regulatory interventions. For this purpose, this project features three building blocks. In the first block, we aim to develop dynamic market models with behavioral consumers. These models are targeted to explain why consumer inertia is so wide-spread in subscription markets, why policy interventions often fail to activate consumers despite large potential switching gains, and why firms that earn high profits per consumer often refrain from offering even better initial deals to consumers. Importantly, we want to understand the role of technological trends (such as declining costs over time), contract design, consumer learning, and regulation restricting what contracts firms can offer in determining the various dynamic price patterns that lead to “loyalty penalties” (i.e. high prices for inactive consumers). In the second block, we plan to empirically analyze how online firms can use their website design (or choice architecture) to influence consumers’ purchase behavior, and combine our empirical insights with theory to determine what the resulting welfare consequences are. As a first step, we combine experimental measures for consumer mistakes and preferences with cookie data to study how consumers’ journeys are affected by the choice architecture of firms. Based on the empirical regularities, we develop behavioral online-market models that allow the firms’ online choice architecture to influence consumer choices. Thereafter, we will reconsider the data in light of our theories in order to quantify the welfare effects of A/B testing. We anticipate that the online data will help us to understand some issues – such as consumer learning or the lack thereof – that will help formulate dynamic market models in building block one. Based on the findings in the first two blocks and in other projects of this research group, the third block considers important policy questions of the digital economy explicitly allowing for behavioral biases, framing effects, and heterogenous consumer responses to inform the ongoing policy debate about online consumer protection as well as the regulation of large online platforms.