Toomas Hinnosaar

We study limited strategic leadership. A collection of subsets covering the leader's action space determines her commitment opportunities. We characterize the outcomes resulting from all possible commitment structures of this kind. If the commitment structure is an interval partition, then the leader's payoff is bounded by her Stackelberg and Cournot payoffs. Under general commitment structures the leader may obtain a payoff that is less than her lowest Cournot payoff. We apply our results to a textbook duopoly model and characterize the commitment structures leading to consumer- and producer-optimal outcomes.

I study price setting within a network of interconnected monopolists. Some firms possess stronger commitment or bargaining power than others, enabling them to influence the pricing decisions of other firms. While it is well-understood that multiple marginalization reduces both total profits and social welfare, I show that strategic interactions within the network exacerbate the marginalization problem. Individual profits are proportional to a new measure of network centrality, defined by the equilibrium characterization. The results underscore the importance of network structure in policy considerations, such as mergers or trade policies.

Top cited article among papers published in TE in 2024.
Additional materials: the code to compute equilibria.
Presentation: recording from CMID20 virtual conference.
Note: In 2016-2017 the paper was circulated under the title .

I study sequential contests where the efforts of earlier players may be disclosed to later players by nature or by design. The model has many applications, including rent seeking, R&D, oligopoly, public goods provision, and tragedy of the commons. I show that information about other players' efforts increases the total effort. Thus, the total effort is maximized with full transparency and minimized with no transparency. I also show that in addition to the first-mover advantage, there is an earlier-mover advantage. Finally, I derive the limits for large contests and discuss the limit to perfectly competitive outcomes under different disclosure rules.

Coverage: Quartz, Guardian, BBC Radio (at 45:00), Telegraph, Independent, Forbes, MSN, IndianExpress, BusinessMagazine (Albanian), Dosja (Albanian), Sustatu (Basque), Dnevnik (Bulgarian), Seznam Zprávy (Chezh), Sina Technology (Chinese), Radio Slobodna Evropa (Croatian), BNNVARA (Dutch), Eesti Ekspress (Estonian), Tivi (Finnish), Business Insider France (French), France Soir (French), Business AM (French), Clubic (French), FR24news (French), Siècle Digital (French), Travelestate (Greek), PiaceProfit (Hungarian), Privátbankár (Hungarian), Morgunblaðið (Icelandic), Daily-planet (Indonesian), Business Insider Italy (Italian), FocusTech (Italian), Gazeta.pl (Polish), 1pezeshk (Persian), Pagina Jornal (Portuguese), Inc. Russia (Russian), National Geographic Rossia (Russian), Nuevo Periodico (Spanish), Forbes Argentina (Spanish), La Información (Spanish), Business Insider Spain (Spanish), Turkish BBC (Turkish), Bursa Hakimiyet (Turkish), Na chasi (Ukrainian).

We document a causal impact of online user-generated information on real-world economic outcomes. In particular, we conduct a randomized field experiment to test whether additional content on Wikipedia pages about cities affects tourists' choices of overnight visits. Our treatment of adding information to Wikipedia increases overnight stays in treated cities compared to non-treated cities. The impact is largely driven by improvements to shorter and relatively incomplete pages on Wikipedia. Our findings highlight the value of content in digital public goods for informing individual choices.

Full title: .
Are there positive or negative externalities in knowledge production? We analyze whether current contributions to knowledge production increase or decrease the future growth of knowledge. To assess this, we use a randomized field experiment that added content to some pages in Wikipedia while leaving similar pages unchanged. We compare subsequent content growth over the next four years between the treatment and control groups. Our estimates allow us to rule out effects on four-year growth of content length larger than twelve percent. We can also rule out effects on four-year growth of content quality larger than four points, which is less than one-fifth of the size of the treatment itself. The treatment increased editing activity in the first two years, but most of these edits only modified the text added by the treatment. Our results have implications for information seeding and incentivizing contributions. They imply that additional content may inspire future contributions in the short- and medium-term but do not generate large externalities in the long term.

The standard model of sequential capacity choices is the Stackelberg quantity leadership model with linear demand. I show that under the standard assumptions, leaders' actions are informative about market conditions and independent of leaders' beliefs about the arrivals of followers. However, this Stackelberg independence property relies on all standard assumptions being satisfied. It fails to hold whenever the demand function is non-linear, marginal cost is not constant, goods are differentiated, firms are non-identical, or there are any externalities. I show that small deviations from the linear demand assumption may make the leaders' choices completely uninformative.

Before purchase, a buyer of an experience good learns about the product's fit using various information sources, including some of which the seller may be unaware of. The buyer, however, can conclusively learn the fit only after purchasing and trying out the product. We show that the seller can use a simple mechanism to best take advantage of the buyer's post-purchase learning to maximize his guaranteed-profit. We show that this mechanism combines a generous refund, which performs well when the buyer is relatively informed, with non-refundable random discounts, which work well when the buyer is relatively uninformed.

Additional materials: Media brief by EJ, Online Appendix.

Risk-neutral sellers can extract high profits from risk-loving buyers by selling them lotteries. To limit risk-taking, gambling is heavily regulated in most countries. I show that protecting risk-loving buyers is essentially impossible.
Even if buyers are risk-loving only asymptotically, the seller can construct a non-random winner-pays auction that ensures unbounded profits. Buyers are asymptotically risk-loving, for example, when their preferences satisfy Savage's axioms or they have cumulative prospect theory preferences. The profits are unbounded even if the seller cannot use any mechanism that resembles a lottery. Asymptotically risk-loving preferences are both sufficient and necessary for unbounded profits.

Selected to Virtual Issue: Editor's Choice Collection by Juuso Välimäki (2019, freely available online).

We consider optimal pricing policies for airlines when passengers are uncertain at the time of ticketing of their eventual willingness to pay for air travel. Auctions at the time of departure efficiently allocate space and a profit maximizing airline can capitalize on these gains by overbooking flights and repurchasing excess tickets from those passengers whose realized value is low. Nevertheless profit maximization entails distortions away from the efficient allocation. Under standard regularity conditions we show that the optimal mechanism can be implemented by a modified double auction. In order to encourage early booking, passengers who purchase late are disadvantaged. In order to capture the information rents of passengers with high expected values, ticket repurchases at the time of departure are at a subsidized price, sometimes leading to unused capacity.

I study a repeated mechanism design problem where a revenue-maximizing monopolist sells a fixed number of service slots to randomly arriving buyers with private values and increasing exit rates. In addition to characterizing the fully optimal mechanism, I study the optimal mechanisms in two restricted classes. First, the pure calendar mechanism, where the seller allocates future service dates instead of general promises. The unique optimal pure calendar mechanism is characterized in terms of the opportunity costs of allocating additional service slots. Second, I analyze the waiting list mechanism, where promises of delayed service can depend on future arrivals, but the seller cannot discriminate among buyers who are offered the same position in the waiting list. Both the waiting list and the fully optimal mechanism are implemented by non-standard auctions with a scoring rule where the distance between buyers' bids affects the allocation. A novel property of these auctions is that for buyers it is better to win by a close margin and it is worse to lose by a close margin. Finally, I model partial commitment power as a penalty that the seller has to pay when forfeiting a promise. All the results are given for general partial commitment and therefore include full commitment and no commitment as special cases.

First version: May 2009.
From 2012-2014 was circulated under the title Penny Auctions are Unpredictable.

This paper studies penny auctions, a novel auction format in which every bid increases the price by a small amount, but placing a bid is costly. Outcomes of real-life penny auctions are often surprising. Even when selling cash, the seller may obtain revenue that is much higher or lower than its nominal value, and losers in an auction sometimes pay much more than the winner. This paper characterizes all symmetric Markov-perfect equilibria of penny auctions and studies penny auctions' properties. The results show that a high variance of outcomes is a natural property of the penny auction format and high revenues are inconsistent with rational risk-neutral participants.

VoxEU column:

Social media influencers account for a growing share of marketing worldwide. We demonstrate the existence of a novel form of market failure in the advertising market: influencer cartels, where groups of influencers collude to increase their advertising revenue by inflating their engagement. Our theoretical model shows that influencer cartels can improve consumer welfare if they expand social media engagement to the target audience, or reduce welfare if they divert engagement to less relevant audiences. Drawing on the model's insights, we empirically examine influencer cartels using novel datasets and machine learning tools, and derive policy implications.

VoxEU column:


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In 2019, North Dakota repealed its Sunday closing law, which had required most non-grocery stores to close between midnight and noon. Using this policy change and consumer GPS data, we study the impact of opening hours on shopping behavior and welfare. We compare visits before and after the repeal in North Dakota and neighboring states using difference-in-differences and event-study designs. The repeal caused a large increase in Sunday morning visits, originating partly from intertemporal, store-type, and cross-border substitution. The closing law's welfare loss is equivalent to increasing the travel distance to affected stores by about 1.4 miles per consumer.

We study a bilateral trade problem where a principal has private information that is revealed with delay, such as a seller who does not yet know her production cost. Postponing the contracting process incurs a costly delay, while early contracting with limited information can create incentive issues, as the principal might misrepresent private information that will be revealed later. We show that the optimal mechanism can effectively address these challenges by leveraging the sequential nature of the problem. The optimal mechanism is a menu of two-part tariffs, where the variable part is determined by the principal's incentives and the fixed part by the agent's incentives. As two-part tariffs might be impractical in some applications, we also study price mechanisms. We show that the optimal price mechanism often entails trade at both the ex-ante and ex-post stages. Dynamic price mechanisms can lower the cost of delay by transacting with high-type agents early and relax the incentive constraints by postponing contracts with lower-type agents. We also generalize our analysis to costly learning and study ex-post efficiency in our context.

I study optimal disclosure policies in sequential contests. A contest designer chooses at which periods to publicly disclose the efforts of previous contestants. I provide results for a wide range of possible objectives for the contest designer. While different objectives involve different trade-offs, I show that under many circumstances the optimal contest is one of the three basic contest structures widely studied in the literature: simultaneous, first-mover, or sequential contest.