Correcting for bias in retrospective data

When panel data are not available, retrospective data are used in the estimation of dynamic choice models. However, retrospective data are not reliable. Previous studies of voting choices, for example, have shown that respondents misreport their past choices in order to appear more consistent with their current choice. Such retrospective bias leads to inconsistent estimates, especially when there is state dependence in choices. Specifically, observed persistence in retrospective data may be due to (a) true state dependence, (b) unobserved heterogeneity, and (c) retrospective bias in reporting previous choices. Whereas Heckman in his 1981 study deals with (a) and (b), we introduce a method to estimate true state dependence while accounting for both unobserved heterogeneity and retrospective reporting bias. Our method is based on modeling the reporting behavior and integrating it into the estimation. The identification strategy is based on the correlation between the reported previous choices and current exogenous variables. Using data on Israeli voters, we find that the probability that a respondent whose vote intention in 1991 differed from his or her past voting choices would lie about their past choices is 0.23. Copyright © 2007 John Wiley & Sons, Ltd.     

Social learning in networks: a Quantal Response Equilibrium analysis of experimental data

Individuals living in society are bound together by a social network and, in many social and economic situations, individuals learn by observing the behavior of others in their local environment. This process is called social learning. Learning in incomplete networks, where different individuals have different information, is especially challenging: because of the lack of common knowledge individuals must draw inferences about the actions others have observed, as well as about their private information. This paper reports an experimental investigation of learning in three-person networks and uses the theoretical framework of Gale and Kariv (Games Econ Behav 45:329–346, 2003) to interpret the data generated by the experiments. The family of three-person networks includes several non-trivial architectures, each of which gives rise to its own distinctive learning patterns. To test the usefulness of the theory in interpreting the data, we adapt the Quantal Response Equilibrium (QRE) model of Mckelvey and Palfrey (Games Econ Behav 10:6–38, 1995; Exp Econ 1:9–41, 1998). We find that the theory can account for the behavior observed in the laboratory in a variety of networks and informational settings. This provides important support for the use of QRE to interpret experimental data.     

Network architecture, cooperation and punishment in public good experiments

Following Fehr and G?echter (Am Econ Rev 90(4):980–994, 2000), a large and growing number of experiments show that public goods can be provided at high levels when mutual monitoring and costly punishment are allowed. Nearly all experiments, however, study monitoring and punishment in a complete network where all subjects can monitor and punish each other. The architecture of social networks becomes important when subjects can only monitor and punish the other subjects to whom they are connected by the network. We study several incomplete networks and find that they give rise to their own distinctive patterns of behavior. Nevertheless, a number of simple, yet fundamental, properties in graph theory allow us to interpret the variation in the patterns of behavior that arise in the laboratory and to explain the impact of network architecture on the efficiency and dynamics of the experimental outcomes.     

Targeted advertising as a signal

This study presents a signaling model of advertising for horizontally differentiated products. The central ingredients of the model are two important characteristics of advertising—targeting, and noisy information content. The theory yields interesting results about the informational role of targeted advertising, and its consequences. First, targeting can itself serve as a signal on product attributes. Second, the effectiveness of targeting depends not only on firms knowing consumer preferences, but on consumers knowing that firms know this. This creates a distinction between strategies of targeting and personalization. Third, the effectiveness of targeting in equilibrium may (far) exceed the information contained directly in the targeted message. Fourth, information content is not, however, superfluous. Specifically, when ads contain no information, a targeting equilibrium does not exist. Together, these results reveal how advertising conveys information both through the content of the message and the firm’s choice of advertising medium. Furthermore, the model is robust to the various critiques of prior work on ads-as-signals: namely, that ad content is irrelevant, ad exposure is unnecessary, and the choice of ads as signals is inherently arbitrary.

(Noisy) communication

Communication is central to many settings in marketing and economics. A focal attribute of communication is miscommunication. We model this key characteristic as a noise in the messages communicated, so that the sender of a message is uncertain about its perception by the receiver, and then identify the strategic consequences of miscommunication. We study a model where competing senders (of different types) can invest in improving the precision of the informative but noisy message they send to a receiver, and find that there exists a separating equilibrium where senders’ types are completely revealed. Thus, although communication is noisy it delivers perfect results in equilibrium. This result stems from the fact that a sender’s willingness to invest in improving the precision of their messages can itself serve as a signal. Interestingly, the content of the messages is ignored by the receiver in such a signaling equilibrium, but plays a central role by shaping her beliefs off the equilibrium path (and thus, enables separation between the types). This result also illustrates the uniqueness of the signaling model presented here. Unlike other signaling models, the suggested model does not require that the costs and benefits of the senders will be correlated with their types to achieve separation. The model’s results have implications for various marketing communication tools such as advertising and sales forces.

Sequential equilibrium in monotone games: A theory-based analysis of experimental data

A monotone game is an extensive-form game with complete information, simultaneous moves and an irreversibility structure on strategies. It captures a variety of situations in which players make partial commitments and allows us to characterize conditions under which equilibria result in socially desirable outcomes. However, since the game has many equilibrium outcomes, the theory lacks predictive power. To produce stronger predictions, one can restrict attention to the set of sequential equilibria, or Markov equilibria, or symmetric equilibria, or pure-strategy equilibria. This paper explores the relationship between equilibrium behavior in a class of monotone games, namely voluntary contribution games, and the behavior of human subjects in an experimental setting. Several key features of the symmetric Markov perfect equilibrium (SMPE) are consistent with the data. To judge how well the SMPE fits the data, we estimate a model of Quantal Response Equilibrium (QRE) [R. McKelvey, T. Palfrey, Quantal response equilibria for normal form games, Games Econ. Behav. 10 (1995) 6-38; R. McKelvey, T. Palfrey, Quantal response equilibria for extensive form games, Exp. Econ. 1 (1998) 9-41] and find that the decision rules of the QRE model are qualitatively very similar to the empirical choice probabilities.     

Marketing and politics: Models, behavior, and policy implications

The American presidential election is one of the largest, most expensive, and most comprehensive marketing efforts. Despite this fact, marketing scholars have largely ignored this campaign, as well as thousands of others for congresspersons, senators, and governors. This article describes the growth of interest in research issues related to political marketing. This emerging research area lies at the crossroads of marketing and political science, but these fields have developed largely independent of one another with little cross-fertilization of ideas. We discuss recent theoretical, empirical, and behavioral work on political campaigns, integrating perspectives from marketing and political science. Our focus is on (1) the extent to which paradigms used in goods and services marketing carry over to the institutional setting of political campaigns, (2) what changes are necessary in models and methodology to understand issues in political marketing and voter behavior, and (3) how the special setting of politics may help us gain a better understanding of certain topics central to marketing such as advertising, branding, and social networks.