Working papers results

Are the players “commonly meta-certain” of an interactive belief model itself? The paper formalizes what it means by: “a player is (meta-)certain of her own belief-generating map” or “the players are (meta-)certain of the profile of belief-generating maps (i.e., the model).” The paper shows: a player is (meta-)certain of her own belief-generating map if and only if her beliefs are introspective. The players are commonly (meta-)certain of the model if and only if, for any event which some player i believes at some state, it is common belief at the state that player i believes the event. This paper then asks whether the “common meta-certainty” assumption is needed for epistemic characterizations of game-theoretic solution concepts. The paper shows: common belief in rationality leads to actions that survive iterated elimination of strictly dominated actions, as long as each player is logical and (meta-)certain only of her own strategy and belief-generating map

Algorithms are becoming the standard tool for bidding in auctions through which digital advertising is sold. To explore how algorithmic bidding might affect functioning of these auctions, this study undertakes a series of simulated experiments where bidders employ Artificial Intelligence algorithms (Q-learning and Neural Network) to bid in online advertising auctions. We consider both the generalized second-price (GSP) auction and the Vickrey-Clarke-Groves (VCG) auction. We find that the more detailed information is available to the algorithms, the better it is for the efficiency of the allocations and the advertisers profit. Conversely, the auctioneer revenues tend to decline as more complete information is available to the advertiser bidding algorithms. We also compare the outcomes of algorithmic bidding to those of equilibrium behavior in a range of different specifications and find that algorithmic bidding has a tendency to sustain low bids both under the GSP and VCG relative to competitive benchmarks. Moreover, the auctioneer revenues under the VCG setting are either close to or lower than those under the GSP setting. In addition, we consider three extensions commonly observed in the data: introduction of a non-stategic player, bidding through a common intermediary, and asymmetry of the information across bidders. Consistent with the theory, the non-strategic player presence leads to increased efficiency, whereas bidding through a common intermediary leads to lower auctioneer revenue compared to the case of individual bidding. Moreover, in experiments with information asymmetry, more informed players earn higher rewards.

We evaluate how traditional parties may respond to populist parties on issues aligning with populist messages. During the 2020 Italian referendum on the reduction of members of Parliament, we conducted a large-scale field experiment, exposing 200 municipalities to nearly a million impressions of programmatic advertisement. Our treatments comprised two video ads against the reform: one debunking populist rhetoric and another attributing blame to populist politicians. This anti-populist campaign proved effective through demobilization, as it reduced both turnout and the votes in favor of the reform. Notably, the effects were more pronounced in municipalities with lower rates of college graduates, higher unemployment, and a history of populist votes. This exogenous influence introduced a unique populist dynamic, observable in the 2022 national election where treated municipalities showed increased support for Brothers of Italy, a rising populist party, and decreased support for both traditional parties and the populists behind the 2020 reform. A follow-up survey further showed increased political interest and diminished trust in political institutions among the residents of municipalities targeted by the campaign.