Strategic Random Networks

To study how economic fundamentals affect the formation of social networks, a model is needed that (i) has agents responding rationally to incentives (ii) can be taken to the data. This paper combines game-theoretic and statistical approaches to network formation in order to develop such a model. Agents spend costly resources to socialize. Their effort levels determine the probabilities of relationships, which are valuable for their direct benefits and also because they lead to other relationships in a second stage of 'meeting friends of friends'. The model predicts random graphs with tunable degree distributions and clustering, and characterizes how those statistics depend on the economic fundamentals. When the value of friends of friends is low, equilibrium networks can be either sparse or thick. But as soon as this value crosses a key threshold, the sparse equilibrium disappears completely and only densely connected networks are possible. This transition mitigates an extreme inefficiency

September 17, 1955 Football Program, UOP vs. Stanford

https://scholarlycommons.pacific.edu/ua-football/1150/thumbnail.jp

September 19, 1953 Football Program, UOP vs. Stanford

https://scholarlycommons.pacific.edu/ua-football/1131/thumbnail.jp

October 3, 1959 Football Program, UOP vs. Stanford

https://scholarlycommons.pacific.edu/ua-football/1271/thumbnail.jp

October 29, 1921 Football Program, UOP vs. Stanford Freshmen

https://scholarlycommons.pacific.edu/ua-football/1548/thumbnail.jp

Manipulation Robustness of Collaborative Filtering Systems

A collaborative filtering system recommends to users products that similar users like. Collaborative filtering systems influence purchase decisions, and hence have become targets of manipulation by unscrupulous vendors. We provide theoretical and empirical results demonstrating that while common nearest neighbor algorithms, which are widely used in commercial systems, can be highly susceptible to manipulation, two classes of collaborative filtering algorithms which we refer to as linear and asymptotically linear are relatively robust. These results provide guidance for the design of future collaborative filtering systems

The Effect Of Entry And Market Structure On Cellular Pricing Tactics

We test the effect of entry on the tariff choices of incumbent cellular firms. We relate the change in the breadth of calling plans between 1996, when incumbents enjoyed a duopoly market, and 1998, when incumbents faced increased competition from personal communications services (PCS) firms. Entry by PCS competitors differed across geographic markets due to the number of licenses left undeveloped as a result of the bankruptcy of some of the auctions’ winning bidders and due to variation across markets in the time required to build a sufficiently large network of wireless infrastructure. We find that incumbents increase tariff variety in markets with more entrants and that this effect is not explained by demographic heterogeneity or cost differences in maintaining calling plans across markets. We also find that incumbents are more likely to upgrade their technology from the old analog technology to the new digital technology in markets with more entry, suggesting that entry also has indirect effects on tariff choice via firms' technology adoption decisions

Congestion and Market Structure in the Airline Industry

Empirical research on the relationship between market congestion and the market competitive level largely falsifies the positive relationship predicted by theoretical models. In this paper, I exploit the airline industry network structure and focus on the level of congestion during periods in which passengers cross-connect to their final destinations. About 70% of hub airport flights depart or land during these periods. The empirical analysis establishes a strong positive relationship. Furthermore, based on a simple theoretical model, I am able to quantify the potential time savings from eliminating congestion externalities and find that, on average, a flight can save 2 minutes of flight time at its departing airport and another 1.5 minutes at its destination airport. I also find that airlines choose to pad their schedule particularly on competitive routes, presumably to attract uninformed passengers