Brett R. Gordon. Contact Information

Transcription

1 Brett R. Gordon Contact Information Education Phone: (412) , GSIA Room 317A Fax: (412) Forbes Avenue Pittsburgh, PA USA Pittsburgh, PA Ph.D., Economics, 2007 (expected) Masters in Information Systems Management, 2002 B.S. (Honors), Economics and Information Systems, 2002 Research Interests Pricing Market Structure Product Innovation and Replacement Entry Models New Products Dissertation A Dynamic Structural Analysis of the PC Processor Industry Dissertation Committee: Ron Goettler (co-chair) Vishal Singh Kannan Srinivasan (co-chair) My dissertation provides a dynamic structural analysis of durable goods demand and competition in industries with rapid technological innovation. Specifically, I examine the market for PC processors, which serve as the brains behind modern computers. This industry is particularly interesting because it is a duopoly, with Intel and Advanced Micro Devices (AMD) controlling about 95 percent of the market. Sales in the PC processor industry have been driven by intense technological innovation and price competition between these two firms, with quality-adjusted prices having fallen about 30 percent per year over the past two decades. To conduct the empirical analysis, I constructed a unique and comprehensive data set including prices, characteristics, sales, and consumer ownership of PC processors over the period from 1993 to 2004, during which market penetration nearly tripled. A detailed history of processor prices and characteristics was assembled from a variety of sources. I supplemented this information with data from market research firms on unit shipments and aggregate survey results on household processor ownership by product. Using this data set, I develop econometric models of consumer demand and firm competition that extend the relevant literatures in empirical industrial organization. I investigate consumer product replacement behavior in the PC processor industry using a structural model of dynamic demand. The replacement decision is inherently dynamic because many durable technology products undergo both rapid improvements in quality and falling prices. First, I show how to incorporate the consumer s replacement decision into a dynamic estimation problem that allows for a sequence of purchases when consumers are uncertain about future product quality and price. Second, I demonstrate how to combine aggregate data on sales and product ownership to infer replacement behavior. The model is solved using generalized method of moments as part of a nested fixed-point procedure that uses a randomized Bellman operator. The empirical analysis reveals several important patterns in how replacement behavior has changed over time as the industry has evolved, and I find significant asymmetries in the competitive relationship between Intel and AMD. Price elasticity estimates from the dynamic model are approximately 30 to 45 percent higher than those produced from a model with myopic consumers. I also demonstrate that the observed increase in the aggregate replacement cycle length is partially due to heterogeneity among consumers with inherently longer replacement cycles. Counterfactual simulations show that the marginal effect of innovation on the replacement

2 cycle length has decreased over time, implying a decline in the ability of quality innovations to generate replacement sales. I also examine the dynamics of the supply-side and firm competition in the PC processor industry using this data set. I combine the dynamic demand structure in the previous case with a dynamic multi-agent game of imperfect competition. Earlier work in dynamic oligopoly models typically assumes consumers act myopically, an assumption that may not be appropriate in durable technology markets. This equilibrium model contains both forward-looking consumers and firms, and controls for the endogeneity of each agents strategies. One particular challenge for this project is creating a computationally tractable model. To this end, I introduce an approximation that retains the critical feature of dynamic demand: price is a dynamic control variable because current sales affect future demand. The Markov-perfect industry equilibrium is estimated using numerical dynamic programming techniques and simulated method of moments. The model allows me to examine the equilibrium effects of dynamic consumer behavior on firms pricing and innovation decisions. I am conducting counterfactual simulations to analyze the equilibrium response of alternative rates of innovation, and to study the degree to which price competition stiffens or softens quality innovation competition. While the model is being applied to the PC processor industry, it is relevant for any durable goods industry where innovation and product obsolescence drive product replacement. Under Review/ Working Papers Replacement Cycles and Innovation in the PC Processor Industry: A Dynamic Structural Approach (under review at Marketing Science). The Seven Percent Illusion? (under review at the RAND Journal of Economics). A Flexible Approach to Estimating Production Functions when Output Prices are Unobserved with Dennis Epple and (to be submitted to American Economic Review). Product Lines and the Product Life Cycle in the CPU Industry with Vishal Singh. Integrating Location-Specific Amenities into Multi-Community Equilibrium Models with Dennis Epple and. Works in Progress Forward-Looking Consumers in a Dynamic Duopoly with Durable Goods with Ron Goettler. Using Blogs to Predict New Product Success with Peter Boatwright and Kannan Srinivasan. Predicting Web Browsing Behavior using a Combination of Clickstream Data and Text Analysis with Alan Montgomery. Local Entry and Competition with Multiple Retail Outlets: The Coffee Shop Industry. Teaching Experience Instructor Quantitative Economic Analysis, Undergraduate Core Course Spring 2004 (4.4/5), Spring 2005 (4.3/5) Teaching Assistant Marketing Research (MBA) Intermediate Microeconomics (Undergraduate) Economic Theory (Undergraduate) Experimental Foundations of Equilibrium (Undergraduate) Labor Economics (Undergraduate) Econometrics II: Generalized Method of Moments (Ph.D.) Econometrics III: Structural Empirical Models in Econometrics (Ph.D.)

3 Teaching Interests Conference Presentations Marketing Research Pricing High-Tech Marketing E-commerce Marketing Marketing Science Conference, Pittsburgh, PA Product Lines and the Product Life Cycle in the CPU Industry International Industrial Organization Conference, Atlanta, GA Estimating a Dynamic Model of Demand for Durable Goods International Industrial Organization Conference, Chicago, IL The Seven Percent Illusion? Honors and Awards Professional Experience Best Ph.D. Student Teacher Award 2004 Graduate Student Research Grant 2004 William Larimer Mellon Fellowship Carnegie Mellon Senior Leadership Award 2002 Phi Kappa Phi 2001 Merck Undergraduate Fellowship 2001 National Society of Collegiate Scholars 2000 Webmind, Inc., New York City, NY Summer 2000 Software Engineer Developed software applications for distributed computational analysis. Infostructure, Inc., Yardley, PA Summer 1999 Systems Analyst Designed and built database systems for clients in healthcare and education. Computer Skills C, C++, Java, Perl, R, S-Plus, SAS, Gauss, SML, Matlab, Mathematica, ArcGIS.

4 Doctoral Coursework Course Econometrics I: Small Sample Theory Econometrics II: Generalized Method of Moments Econometrics III: Discrete-Choice Models Econometrics IV: Structural Econometric Models Marketing Seminar II: Advanced Choice Models Marketing Seminar III: Analytical and Structural Marketing Models Nonparametric and Semi-nonparametric Econometrics Dynamic Empirical Models in Industrial Organization Mathematics for Economists Microeconomic Theory Game Theory Contract Theory Economics of Education General Equilibrium Dynamic Competitive Analysis Macroeconomics: Real Business Cycles Macroeconomics: Monetary Theory Estimation of Continuous-Time Finance Models Mathematical Probability and Statistics I & II Intermediate Statistics Advanced Probability Theory Applied Bayesian and Computational Statistics Real Analysis Machine Learning Information Retrieval Instructor Fallaw Sowell Mark Manuszak Baohong Sun Kannan Srinivasan George-Levi Gayle Ronald Goettler Robert Miller Uday Rajan Bruno Biais Dennis Epple Steve Spear Daniele Coen-Pirani Finn Kydland Bennett McCallum Fallaw Sowell Larry Wasserman Chris Genovese Mark Schervish Brian Junker William Hrusa Andrew Moore Yiming Yang References Ronald Goettler (co-chair) Kannan Srinivasan (co-chair) Associate Professor of Economics H.J. Heinz II Professor Pittsburgh, PA Pittsburgh, PA Phone: (412) Phone: (412) rong@andrew.cmu.edu kannans@andrew.cmu.edu Vishal Singh Assistant Professor of Marketing Professor of Economics Pittsburgh, PA Pittsburgh, PA Phone: (412) Phone: (412) vsingh@andrew.cmu.edu holgers@andrew.cmu.edu Alan Montgomery Dennis Epple Associate Professor of Marketing Thomas Lord Professor of Economics Pittsburgh, PA Pittsburgh, PA Phone: (412) Phone: (412) alm3@andrew.cmu.edu epple@andrew.cmu.edu

5 Abstracts of Working Papers Replacement Cycles and Innovation in the PC Processor Industry: A Dynamic Structural Approach (under review at Marketing Science). Innovation drives consumers to replace their existing products in many technology industries. However, the replacement decision has received little attention in both marketing and economics in the context of durable technology markets. This decision is inherently dynamic because the consumer that forgoes a purchase today might buy a potentially better product tomorrow for less money. In this paper, I develop and estimate a dynamic consumer demand model that explicitly accounts for the replacement decision when consumers are uncertain about both future product quality and price. Using a unique data set from the PC processor industry, I investigate the relationship between consumer replacement behavior and product innovation. The empirical analysis reveals several important patterns in how replacement behavior has changed over time as the industry has evolved, and I find significant asymmetries in the competitive relationship between Intel and AMD. Price elasticity estimates from the dynamic model are approximately 30 to 45 percent higher than those produced from a model with myopic consumers. I also demonstrate that the observed increase in the aggregate replacement cycle length is partially due to the presence of more consumers with inherently longer replacement cycles. Counterfactual simulations show that the marginal effect of innovation on the replacement cycle length has decreased over time, implying a decline in the ability of quality innovations to generate replacement sales. Forward-Looking Consumers in a Dynamic Duopoly with Durable Goods with Ron Goettler. Dynamic models of multi-agent games are increasingly being used in marketing and economics to analyze competition in oligopolies. These models typically assume consumers act myopically, an assumption that may not be appropriate in durable technology markets. This paper builds an equilibrium model of imperfect competition with both forward-looking consumers and firms operating in a durable goods industry. To make the model tractable, we introduce an approximation that retains the critical feature of dynamic demand: price is a dynamic control variable because current sales affect future demand. We apply the model to the PC processor industry because the industry is a duopoly with high levels of innovation and price competition. We solve for a Markov-perfect industry equilibrium using numerical dynamic programming techniques, and estimate the model with simulated method of moments. The model allows us to examine the equilibrium effects of dynamic consumer behavior on firms price and innovation decisions. We also conduct counterfactual simulations to study how much price competition stiffens or softens quality innovation competition, and to analyze the equilibrium response of alternative rates of innovation. While the model is being applied to the PC processor industry, its implications should be relevant for any durable goods industry where innovation and product obsolescence drive product replacement.

6 The Product Line and Life Cycle in the PC Processor Industry with Vishal Singh. This paper investigates the determinants of the product life cycle in the PC processor industry. This industry is particularly interesting because it is composed of two major players, Intel and AMD, engaged in a long competitive battle in terms of both technology and pricing. Using a unique data set covering the period from 1993 to 2005, we examine the rate of product introduction and turnover using four types of factors: product characteristics, product line features, competitor s products, and market/industry factors. Our analysis reveals several asymmetries between the industry and firm level results. At the industry level, we find that product line size has increased over time, and that larger product lines tend to experience greater product turnover. The rate of product introduction also increased as the technology gap between the two firms shrank. At the firm level, we find that product life cycles behaved differently depending on whether the firm was the technology leader. Consistent with the notion that Intel was the dominant firm over the sample, the model s estimates show that AMD is more sensitive to both cannibalization and the competitor s product line. The Seven Percent Illusion? (under review at the RAND Journal of Economics). From 1995 to 1998, more than 90 percent of mid-range IPOs had underwriter fees, or spreads, of exactly seven percent, although evidence suggests that economies of scale in the size of the offering should allow for lower fees. Chen and Ritter (2000) offer collusion as a possible explanation based on empirical analysis and observation. Alternatively, I investigate whether the spreads may not be the result of collusion, but instead, arise from strategic behavior on the part of the underwriters. I build a model that captures several important characteristics of competition in the IPO industry, such as differentiation among underwriters in their reputation and ability to screen potential entrepreneurs. In equilibrium, as the underlying distribution of entrepreneurs becomes increasingly skewed towards larger firms, I demonstrate that underwriters may charge approximately the same spread to entrepreneurs of different valuations. Thus, the model produces a pricing pattern that is consistent with observation, and does so in a strategic environment. A Flexible Approach to Estimating Production Functions When Output Prices are Unobserved with Dennis Epple and (to be submitted to American Economic Review). A significant amount of price dispersion exists in many industries. As a consequence, the value of output is not necessarily a good measure of the quantity of output. Estimation of production functions for these types of goods is thus challenging, since quantities and prices of output are typically not separately observed by the econometrician. This paper provides a new flexible approach for estimating production functions which treats quantity and prices for output as latent variables. To illustrate the usefulness of the techniques we consider two applications. The first application focuses on estimating production functions for housing. The empirical analysis is based on a comprehensive database of recently built properties in Allegheny County, Pennsylvania. The second application focuses on the car repair service industry based on a unique survey conducted by the leading industry magazine. We find that the new methods proposed in this paper work well in these applications and provide reasonable estimates for the underlying production functions.

7 Integrating Location-Specific Amenities into Multi-Community Equilibrium Models with Dennis Epple and. Multi-community equilibrium models of housing choice often ignore heterogeneity among locations in metropolitan areas. In such models, household preferences for location are driven by differences in publicly provided goods and tax rates across jurisdictions in the metropolitan area. From the perspective of both empirical research and policy analysis, this abstraction is naturally of concern because location-specific amenities proximity to local business centers, an abundance of trees, or a quiet street often have a significant impact on housing choice. In this paper, we provide conditions under which models that assume a single housing price in each community continue to apply in the presence of location-specific amenities that vary both within and across communities. We then show how this framework yields a straightforward empirical method for estimating amenity levels and housing prices across communities and provides a useful tool that facilitates policy analysis.