Estimating Product Characteristics and Spatial Competition in the Network Television Industry

Assessing the demand for products with characteristics that are unobservable or difficult to measure is becoming increasingly important with the growing proliferation and value of such products. Analyzing industry performance and firm competition in these sectors is hindered by the failure of traditional empirical methods to estimate demand for the products of these sectors. This paper focuses on the network television industry to present: (a) an empirical analysis of spatial competition, and (b) a structural approach to estimating product characteristics and consumer preferences in such industries, and (c) optimal network programming and scheduling given the estimated demand system. We use maximum simulated likelihood to estimate a structural model of viewer choice, yielding estimates of the latent characteristics of each show, the distribution of consumers' preferences for these characteristics, and the state dependence of choices. Results indicate the attribute space spans four dimensions of horizontal differentiation and one vertically differentiated dimension. Interpretations of these dimensions reflect the traditional show labels. For example, one of the dimensions represents the degree of realism in a show. Furthermore, the clustering of shows based on the estimated characteristics corresponds to traditional show labels. We identify four clusters --- sitcoms for mature viewers, sitcoms for younger viewers, reality based dramas, and fictional dramas. Regarding strategic behavior, our model suggests the networks should use counter-programming (i.e., differentiated products) within each time slot and homogeneous programming through each night. The estimated show locations reveal an extensive use of these strategies, as well as a limited degree of branding. Nonetheless, by unilaterally changing their schedules to increase both counter-programming and homogeneity, ABC, CBS, and NBC are able to increase their weekly ratings by 16%, 12%, and 15%, respectively. In a Nash equilibrium of the static scheduling game, these gains are reduced to 15%, 6%, and 12% increases.

Information acquisition in a limit order market

Abstract We model an infinite horizon trading game of a limit order market with informed traders. Agents with a private and common value motive for trade randomly arrive in a market and may either post prices (submit limit orders) or accept posted prices (submit market orders). If their orders have not executed, traders may reenter the market and thus solve a dynamic problem. We consider agents' incentive to acquire information. We characterize how information acquisition changes agents' strategies and demonstrate the effect of this on the efficiency of market prices. We demonstrate that for some costs of acquiring information, there are multiple equilibria in the information acquisition game. Finally, we demonstrate that information acquisition can make all agents worse off

Tariff Choice with Consumer Learning: Sorting-Induced Biases and Illusive Surplus

Firms often offer menus of two-part tariffs to price discriminate among consumers with heterogeneous preferences. In this paper we study the effectiveness of this screening mechanism when consumers are uncertain about the quality of the good and resolve this uncertainty through consumption experiences. We use consumer-level data to estimate a dynamic structural model of forward-looking consumers with heterogeneous demands, both ex-ante and ex-post, for an experience good sold by a monopolist offering a fixed menu of two-part tariffs. Our analysis highlights three elements that influence consumer behavior and affect pricing strategies: beliefs, experiential learning, and switching costs. We test the rational expectations assumption against a weaker assumption about beliefs that retains unbiasedness, on average across all consumers, but allows beliefs to be biased conditional on tariff choice. The rational expectations assumption is rejected: consumers on flat fee tariffs tend to have optimistic priors whereas consumers on per-use tariffs tend to have pessimistic priors. If switching costs are sufficiently high, this sorting-induced bias implies that flat fee tariffs can yield high profits for the firm even after optimistic consumers revise their beliefs. This dynamic lock-in effect of flat fees augments their traditional role in static settings of extracting consumer surplus. Biased priors also lead to biased expectations of consumer surplus. Realized surplus is on average negative, despite expectations of a large and positive discounted lifetime surplus.