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In the first chapter, I measure the effects of street-level political advertising on voting behavior. I use a novel dataset on ad location in a major Spanish city during elections for the national parliament as well as granular socio-economic and voting data. This set-up, where more than two parties are running for office and elections are very competitive, allows me to explore the heterogeneous effects of ads across parties as well as how parties' ads affect other parties' vote shares. To identify the effects of parties' ads, I exploit a legally mandated randomized assignment of ad location to parties across multiple years. I find that a party's own ads have a positive effect on its vote share, although the effects are heterogeneous across parties. A one standard deviation increase in the number of ads increases a party's vote share by 0.79 percentage points on average. Ads of parties with ideologically distant platforms consistently have a negative effect on a party's vote share. In contrast, ads of parties that are close competitors may act either as complements or substitutes in different years. The second chapter analyses the effects of an economic shock on the emergence of new parties and other changes in voting parties by using regional variation in the exposure to the shock. I find that a worsening of economic conditions as measured by unemployment rate leads to an increase in electoral competition and volatility. In particular, the deeper the effects of the recession in a area, the larger the number of new parties emerge and become more successful and there is an increase in the changes in vote shares. On the other hand, the vote share of parties previously in government decreases and a decrease in vote share concentration. The third chapter is a co-authored works where we present experimental evidence establishing that the level of incentives affects both gameplay and beliefs. Holding fixed the actions of the other player, we find that, in the context of dominance-solvable games, higher incentives make subjects more likely to best-respond to their beliefs. Moreover, higher incentives result in more responsive beliefs but not necessarily less biased. We provide evidence that incentives affect effort and that it is effort, and not incentives directly, that accounts for the changes in belief formation. The results support models where, in addition to choice mistakes, players exhibit costly attention.

EverQuest is a multiplayer online role playing game that serves as a practical incarnation of life as a cyborg in a posthuman community. Using cultural materialsim, this thesis demonstrates how the words of EverQuest interactants - from message boards, interviews, and player in-game communications - construct the world of EverQuest and the roles of the interactants as its citizens. More specifically, this thesis will argue that the EverQuest world serves to reify the ideas of consumer capitalism that informs the "real" world, even as EverQuest itself promises an escape from that world.

In marketing and other social sciences, researchers often use field data to empirically study how people make decisions in naturalistic environments. There are numerous theoretical and practical challenges to doing so, and in this dissertation, I propose methodological approaches to address two such challenges. First, people often make complex decisions that are described in terms of high-dimensional or unstructured variables (e.g., writing text or choosing an assortment from a large set of options) which are difficult to analyze relative to simpler decisions (e.g., binary choices). Second, when analyzing how people's decisions are affected by a major event (e.g., regulatory changes or a global pandemic), events often affect a large population of interest simultaneously, making it difficult to assess the impact of the event relative to a counterfactual where the event did not occur. In Chapter 1, I address the first challenge in the context of non-cooperative games. I develop a novel neural network architecture that enables behavioral analysis of complex games by estimating a game's payoff structure (e.g., win probabilities between pairs of actions) while simultaneously mapping agent actions to a lower-dimensional latent space that encodes strategic similarities between actions in a smooth, linear manner. I apply my method to analyze a unique dataset of over 11 million matches played in a competitive video game with a large array of actions and complex strategic interactions. I find that players select actions that counterfactually would have performed better against recent opponents, demonstrating model-based reasoning. Still, players overrely on simple heuristics relative to model-based reasoning to an extent that is similar to findings reported in lab settings. I find that noisy and biased decision-making leads to frequent selection of suboptimal actions, which corresponds to lower player engagement. This demonstrates the limits of player sophistication when making complex competitive decisions and suggests that platforms hosting competitions may benefit from interventions that enable players to improve their decision-making. In Chapter 2, I address the second challenge, proposing a general and flexible methodology for inferring the time-varying effects of a discrete event on consumer behavior when the event spans the target population being analyzed, such that there is no contemporaneous "control group" and/or it is not possible to measure treatment status. I achieve identification by exploiting the empirical regularity of customer spending patterns across cohorts (i.e., groups of customers who adopted the same product or service at different times), comparing purchasing behavior across cohorts who were affected by the event at different points in their tenure. My method applies nonparametric age-period-cohort (APC) models, commonly used in sociology but with limited adoption in marketing, in conjunction with a predictive model of the counterfactual no-event baseline (i.e., an event study model). I use this method to infer how the COVID-19 pandemic has affected 12 online and offline consumption categories. My results suggest that the pandemic initially drove significant spending lifts at e-commerce businesses at the expense of brick-and-mortar alternatives. After two years, however, these changes have largely reverted. I observe significant heterogeneity across categories, with more persistent changes in subscription-based categories and more transient changes in categories based on discretionary purchases, especially those of durable goods.

The general topic of our thesis is forward looking behavior in strategic situations. Mixing theoretical and experimental analysis, we document how strategic thinking is affected by the specific features of a dynamic interaction. The overarching result is that the information regarding decisions that are close to the current one, receive a qualitatively different consideration, with respect to distant ones. That is, the actual decisions are based on reasoning over a limited number of steps, close to actual decison node. We capture this feature of behavior both in a strategic (limited backward induction) and in a non-strategic (limited farsightedness) set up, and we identify relevant consequences on the outcome of the interaction, which powerfullly explain many observed experimental regularities.<p>In the first essay, we present a general out-of-equilibrium framework for strategic thinking in sequential games. It assumes the agents to take decisions on restricted game trees, according to their (limited) foresight level, following backward induction. Therefore we talk of limited backward induction (LBI). We test for LBI using a variant of the race game. Our design allows to identify restricted game trees and backward reasoning, thus properly disentangling LBI behavior. The results provide strong support in favor of LBI. Most players solve intermediate tasks - i.e. restricted games - without reasoning on the terminal histories. Only a small fraction of subjects play close to equilibrium, and (slow) convergence toward it appears, though only in the base game. An intermediate task keeps the subjects off the equilibrium path longer than in the base game. The results cannot be rationalized using the most popular models of strategic reasoning, let alone equilibrium analysis.<p>In the second essay, a subtle implication of the model is investigated: the sensitivity of the players’ foresight to the accessibility and completeness of the information they have, using a Centipede game. By manipulating the way in which information is provided to subjects, we show that reduced availability of information is sufficient to shift the distribution of take-nodes further from the equilibrium prediction. On the other hand, similar results are obtained in a treatment where reduced availability of information is combined with an attempt to elicit preferences for reciprocity, through the presentation of the centipede as a repeated trust game. Our results could be interpreted as cognitive limitations being more effective than preferences in determining (shifts in) behavior in our experimental centipede. Furthermore our results are at odds with the recent ones in Cox [2012], suggesting caution in generalizing their results. Reducing the availability of information may hamper backward induction or induce myopic behavior, depending on the strategic environment.<p>The third essay consists of an experimental investigation of farsighted versus myopic behavior in network formation. Pairwise stability Jackson and Wolinsky [1996] is the standard stability concept in network formation. It assumes myopic behavior of the agents in the sense that they do not forecast how others might react to their actions. Assuming that agents are perfectly farsighted, related stability concepts have been proposed. We design a simple network formation experiment to test these extreme theories, but find evidence against both of them: the subjects are consistent with an intermediate rule of behavior, which we interpret as a form of limited farsightedness. On aggregate, the selection among multiple pairwise stable networks (and the performance of farsighted stability) crucially depends on the level of farsightedness needed to sustain them, and not on efficiency or cooperative considerations. Individual behavior analysis corroborates this interpretation, and suggests, in general, a low level of farsightedness (around two steps) on the part of the agents. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished