Book Description

The dissertation consists of three essays on applied theory with a particular focus on industrial organization applications. The first chapter develops and analyzes a dynamic stochastic model for a firm with limited managerial attention that is spent either on expansion or on improving quality of product. Under a reputational framework, I characterize how the incentives for expansion and innovation depend on a firm's current reputation, quality, and capacity. Intuitively, from the firm's perspective, quality and capacity are complements; the incentive to improve one increases with the level of the other. Thus, the firm innovates when its quality is low, reputation is low, and capacity is high; the firm expands when its quality is high, reputation is high, and capacity is low. In the second chapter, I investigate several model variants of the reputational model proposed in Chapter 1. First, I introduce a non-trivial cost of innovation and expansion. I show that in equilibrium, the firm's optimal strategy takes an "innovate-shirk-expand" shape. In the second model variant, I replace the strong linearity assumption with increasing/decreasing returns to scale. Consequently, capacity becomes effective in the information structure. I show that, on each equilibrium path, the firm innovates when its quality is low, reputation is low, and capacity is high; it expands when its quality is high, reputation is high, and capacity is low. Finally, I generalize this model to a continuum of firms and study the steady-state distribution of reputation, quality, and capacity. Both computational and numerical results show that the bulk of low-reputation, low-quality firms lie at the bottom, while a few pioneers with high quality and high capacity are found at the top. In the third chapter, I study the competition between two firms for a two-stage research and development project, where the difficulty of the first stage is unknown. I assume that each firm holds a belief concerning the difficulty of stage 1 and updates its belief following Bayes' rule. Firm can choose to report or withhold their intermediate results. I show that, as the exit point approaches, the firm has an incentive to conceal its success in the first stage, in the hope that its opponent raises its estimation of the stage's difficulty and soon exits. I demonstrate the existence of a unique equilibrium, characterize the firm's optimal strategy for report, withhold, and exit decisions, and investigate the resulting firm dynamics.