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Employee knowledge is a critical contributor to the quality of output in knowledge-intensive industries. A debated but unresolved question is whether the resources provided by firms in knowledge-intensive industries contribute to the observed variation in employees' performance across firms. The answer to this question is unclear because the benefits from the resources that firms provide may be competed away or transferred to the employees when they leave the firm. I provide evidence on this question by analyzing the equity research industry.
Previous research has investigated what happens when customers start utilizing more than a single sales channel (i.e., become multichannel). This research stream has identified two key consequences of multichannel usage. First, Shankar et al. (2003) and Hitt and Frei (2002) determine that customers using an internet channel in addition to the traditional brick-and-mortar channel are more loyal than customers who use a single channel.
This dissertation consists of three chapters related to issues in corporate credit. The first chapter studies whether credit rating agencies applied consistent rating standards to U.S. corporate bonds over the expansion and recession periods between 2002 and 2011. Based on estimates of issuing firms' credit quality from a structural model, I find that rating standards are in fact procyclical: ratings are stricter during an economic downturn than an expansion. As a result, firms receive overly pessimistic ratings in a recession, relative to during an expansion.
Infrastructure systems play a crucial role in our daily lives. They include, but are not limited to, the highways we take while we commute to work, the stadiums we go to watch games, and the power plants that provide the electricity we consume in our homes. In this thesis we study infrastructure systems from several different perspectives with a focus on pricing and scalability. The pricing aspect of our research focuses on two industries: toll roads and sports events. Afterwards, we analyze the potential impact of small modular infrastructure on a wide variety of industries.
Recent technological developments allow the online collection of valuable information that can be efficiently used to optimize decisions "on the fly" and at a low cost. These advances have greatly influenced the decision-making process in various areas of operations management, including pricing, inventory, and retail management. In this thesis we study methodological as well as practical aspects arising in online sequential optimization in the presence of such real-time information streams.
The first essay examines whether risk is explained based on cash flow (CF) or discount rate (DR). Realized returns comprise (ex-ante) expected returns plus (ex-post) innovations, and consequently both expected returns and returns innovations can be broken down into components reflecting fluctuations in CF and DR. I use a present-value model to identify the CF and DR risk factors which are latent from the time series and cross sections of price-dividend ratios.
Unlike other costs of trading, capital gains taxes are not well understood. The tax cost of selling an asset includes the present value change in current and future tax liabilities caused by the sale. Investors paying a positive capital gains tax often face a negative tax cost of selling, thanks to other features of the tax code that are inextricably linked to the existence of capital gains taxes: depreciation or amortization allowances.
This dissertation introduces a new method for evaluating mergers and acquisitions (M&As) and goodwill allocations associated with them. This method differs from Generally Accepted Accounting Principles (GAAP), which estimate the sum of the fair value of net identifiable assets by focusing on balance sheet information, and recognizes the remainder of the purchase price as goodwill. The new method utilizes both balance sheet and income statement information to estimate the value of a target as a business, and treats the remainder of the purchase price as the uncertain growth expectation.
This dissertation contains two essays examining the role of attention and information processing in stated choices under choice-based preference measurement tasks. While choice experiments have long been used in marketing as a way to measure con- sumer preferences, full rationality of consumers is always assumed, meaning consumers are able to process all the choice relevant information before making a decision.
This dissertation delves into the relation between asset returns, risks, and cash flow expectations. The first chapter uses the model-implied patterns of cash flow expectations to differentiate among the three most prominent behavioral theories explaining stock return momentum and reversal. Using analyst earnings forecasts as a proxy for cash flow expectations, I trace the dynamics of the expectation errors for winner and loser stocks in a 24-month holding period, during which returns are characterized by a momentum phase followed by a reversal phase.