The Effects of Social Ties on Coordination: Conceptual Foundations for an Empirical Analysis

International audienceThis paper investigates the influence that social ties can have on behavior. After defining the concept of social ties that we consider, we introduce an original model of social ties. The impact of such ties on social preferences is studied in a coordination game with outside option. We provide a detailed game theoretical analysis of this game while considering various types of players, i.e., self-interest maximizing, inequity averse, and fair agents. In addition to these approaches that require strategic reasoning in order to reach some equilibrium, we also present an alternative hypothesis that relies on the concept of team reasoning. After having discussed the differences between the latter and our model of social ties, we show how an experiment can be designed so as to discriminate among the models presented in the paper

A practitioner's guide to Bayesian estimation of discrete choice dynamic programming models

This paper provides a step-by-step guide to estimating infinite horizon discrete choice dynamic programming (DDP) models using a new Bayesian estimation algorithm (Imai et al., Econometrica 77:1865–1899, 2009a) (IJC). In the conventional nested fixed point algorithm, most of the information obtained in the past iterations remains unused in the current iteration. In contrast, the IJC algorithm extensively uses the computational results obtained from the past iterations to help solve the DDP model at the current iterated parameter values. Consequently, it has the potential to significantly alleviate the computational burden of estimating DDP models. To illustrate this new estimation method, we use a simple dynamic store choice model where stores offer “frequent-buyer” type rewards programs. Our Monte Carlo results demonstrate that the IJC method is able to recover the true parameter values of this model quite precisely. We also show that the IJC method could reduce the estimation time significantly when estimating DDP models with unobserved heterogeneity, especially when the discount factor is close to 1

Advertising Bans and the Substitutability of Online and Offline Advertising

The authors examine whether the growth of the Internet has reduced the effectiveness of government regulation of advertising. They combine nonexperimental variation in local regulation of offline alcohol advertising with data from field tests that randomized exposure to online advertising for 275 different online advertising campaigns to 61,580 people. The results show that people are 8% less likely to say that they will purchase an alcoholic beverage in states that have alcohol advertising bans compared with states that do not. For consumers exposed to online advertising, this gap narrows to 3%. There are similar effects for four changes in local offline alcohol advertising restrictions when advertising effectiveness is observed both before and after the change. The effect of online advertising is disproportionately high for new products and for products with low awareness in places that have bans. This suggests that online advertising could reduce the effectiveness of attempts to regulate offline advertising channels because online advertising substitutes for (rather than complements) offline advertising.Google (Firm)WPP (Firm

A Thematic Approach to User Similarity Built on Geosocial Check-ins

Abstract. Computing user similarity is key for personalized locationbased recommender systems and geographic information retrieval. So far, most existing work has focused on structured or semi-structured data to establish such measures. In this work, we propose topic modeling to exploit sparse, unstructured data, e.g., tips and reviews, as an additional feature to compute user similarity. Our model employs diagnosticity weighting based on the entropy of topics in order to assess the role of commonalities and variabilities between similar users. Finally, we offer a validation technique and results using data from the locationbased social network Foursquare