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Dive into the research topics where Brett R. Gordon is active.

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Featured researches published by Brett R. Gordon.


Journal of Political Economy | 2011

Does AMD Spur Intel to Innovate More

Ronald L. Goettler; Brett R. Gordon

We estimate an equilibrium model of dynamic oligopoly with durable goods and endogenous innovation to examine the effect of competition on innovation in the personal computer microprocessor industry. Firms make dynamic pricing and investment decisions while consumers make dynamic upgrade decisions, anticipating product improvements and price declines. Consistent with Schumpeter, we find that the rate of innovation in product quality would be 4.2 percent higher without AMD present, though higher prices would reduce consumer surplus by


Marketing Science | 2009

A Dynamic Model of Consumer Replacement Cycles in the PC Processor Industry

Brett R. Gordon

12 billion per year. Comparative statics illustrate the role of product durability and provide implications of the model for other industries.


Journal of Marketing Research | 2013

Does Price Elasticity Vary with Economic Growth? A Cross-Category Analysis

Brett R. Gordon; Avi Goldfarb; Yang Li

As high-tech markets mature, replacement purchases inevitably become the dominant proportion of sales. Despite the clear importance of product replacement, little empirical work examines the separate roles of adoption and replacement. A consumers replacement decision is dynamic and driven by product obsolescence because these markets frequently undergo rapid improvements in quality and falling prices. The goal of this paper is to construct a model of consumer product replacement and to investigate the implications of replacement cycles for firms. To this end, I develop and estimate a dynamic model of consumer demand that explicitly accounts for the replacement decision when consumers are uncertain about future price and quality. Using a unique data set from the PC processor industry, I show how to combine aggregate data on sales and product ownership to infer replacement behavior. The results reveal substantial variation in replacement behavior over time, and this heterogeneity provides an opportunity for managers to tailor their product introduction and pricing strategies to target the consumers of a particular segment that are most likely to replace in the near future.


Journal of Regional Science | 2010

Drs. muth and mills meet dr. Tiebout: Integrating location-specific amenities into multi-community equilibrium models

Dennis Epple; Brett R. Gordon; Holger Sieg

How does price sensitivity change with the macroeconomic environment? The authors explore this question by measuring price elasticity using household-level data across 19 grocery categories over 24 quarters. For each category, they estimate a separate random coefficients logit model with quarter-specific price response parameters and control functions to address endogeneity. This specification yields a novel set of 456 elasticities across categories and time that are generated using the same method and therefore can be directly compared. On average, price sensitivity is countercyclical: It rises when the macroeconomy weakens. However, substantial variation exists, and a handful of categories exhibit procyclical price sensitivity. The authors show that the relationship between price sensitivity and macroeconomic growth correlates strongly with the average level of price sensitivity in a category. They examine several explanations for this result and conclude that a categorys share of wallet is the more likely driver versus alternative explanations based on product perishability, substitution across consumption channels, or market power.


Marketing Science | 2011

Competitive Strategy for Open Source Software

Vineet Kumar; Brett R. Gordon; Kannan Srinivasan

We consider the problem of integrating spatial amenities into locational equilibrium models with multiple jurisdictions. We provide sufficient 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. If these conditions are satisfied, the models, estimation methods, and results in Epple and Sieg (1999) are valid in the presence of (potentially unobserved) location-specific amenities. We also show how to construct sufficient statistics that capture location specific spatial heterogeneity. We apply these techniques using data from the Pittsburgh metropolitan area. We find that these amenity measures capture proximity to important local employment centers as well as heterogeneity in school quality within a given school district.


Marketing Science | 2015

A Dynamic Model of Rational Addiction: Evaluating Cigarette Taxes

Brett R. Gordon; Baohong Sun

Commercial open source software (COSS) products---privately developed software based on publicly available source code---represent a rapidly growing, multibillion-dollar market. A unique aspect of competition in the COSS market is that many open source licenses require firms to make certain enhancements public, creating an incentive for firms to free ride on the contributions of others. This practice raises a number of puzzling issues. First, why should a firm further develop a product if competitors can freely appropriate these contributions? Second, how does a market based on free riding produce high-quality products? Third, from a public policy perspective, does the mandatory sharing of enhancements raise or lower consumer surplus and industry profits? We develop a two-sided model of competition between COSS firms to address these issues. Our model consists of (1) two firms competing in a vertically differentiated market, in which product quality is a mix of public and private components, and (2) a market for developers that firms hire after observing signals of their contributions to open source. We demonstrate that free-riding behavior is supported in equilibrium, that a mandatory sharing setting can result in high-quality products, and that free riding can actually increase profits and consumer surplus.


Social Science Research Network | 2017

A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook

Brett R. Gordon; Florian Zettelmeyer; Neha Bhargava; Dan chapsky

Addiction creates an intertemporal link between a consumers past and present decisions, altering their responsiveness to price changes relative to nonaddictive products. We construct a dynamic model of rational addiction and endogenous consumption to investigate how consumers respond to policy interventions that aim to reduce purchases of cigarettes. We find that, on average, the category elasticity is about 35% higher when the model correctly accounts for addiction. However, some policies spur substitution from more expensive single packs to less expensive cartons of cigarettes, resulting in higher overall consumption for some consumers.


Proceedings of the National Academy of Sciences of the United States of America | 2018

Field studies of psychologically targeted ads face threats to internal validity

Dean Eckles; Brett R. Gordon; Garrett A. Johnson

Measuring the causal effects of digital advertising remains challenging despite the availability of granular data. Unobservable factors make exposure endogenous, and advertising’s effect on outcomes tends to be small. In principle, these concerns could be addressed using randomized controlled trials (RCTs). In practice, few online ad campaigns rely on RCTs, and instead use observational methods to estimate ad effects. We assess empirically whether the variation in data typically available in the advertising industry enables observational methods to recover the causal effects of online advertising. Using data from 15 US advertising experiments at Facebook comprising 500 million user-experiment observations and 1.6 billion ad impressions, we contrast the experimental results to those obtained from multiple observational models. The observational methods often fail to produce the same effects as the randomized experiments, even after conditioning on extensive demographic and behavioral variables. In our setting, advances in causal inference methods do not allow us to isolate the exogenous variation needed to estimate the treatment effects. We also characterize the incremental explanatory power our data would require to enable observational methods to successfully measure advertising effects. Our findings suggest that commonly used observational approaches based on the data usually available in the industry often fail to accurately measure the true effect of advertising.


Marketing Science | 2011

Foreword---Revisiting the Workshop on Quantitative Marketing and Structural Econometrics

Brett R. Gordon; Raphael Thomadsen; Eric T. Bradlow; Jean-Pierre Dubé; Richard Staelin

We applaud Matz et al. (1) for using field studies on Facebook to investigate the effectiveness of psychologically targeted messages, building on prior, largely laboratory-based research. That said, this comparison of Facebook ad campaigns does not randomly assign users to conditions, which threatens the internal validity of their findings and weakens their conclusions. The paper uses Facebook’s standard ad platform to compare how different versions of ads perform. However, this process does not create a randomized experiment: users are not randomly assigned to different ads, and individuals may even receive multiple ad types (e.g., both extroverted and introverted ads). Furthermore, ad platforms like Facebook optimize campaign performance by showing ads to users whom the platform expects are more likely to fulfill the campaign’s objective (e.g., study 1, online … [↵][1]2To whom correspondence should be addressed. Email: dean{at}deaneckles.com. [1]: #xref-corresp-1-1


Archive | 2018

Digitization and Distribution: The Ends Against the Middle

Joonhyuk Yang; Eric T. Anderson; Brett R. Gordon

This foreword and the subsequent four invited articles were commissioned by Eric T. Bradlow while Editor-in-Chief of Marketing Science. The foreword was written in four parts; each part covers a different aspect of the Workshop on Quantitative Marketing and Structural Econometrics. The workshop was cosponsored by Columbia Business School, Duke University, the University of California at Los Angeles, and the INFORMS Society for Marketing Science and was held at the Fuqua School of Business at Duke University in August 2010. The introductory section, written by Bradlow, covers why he commissioned these articles in the first place. In his section, Jean-Pierre Dube discusses “going from good to great” in the structural econometrics area as applied to marketing problems. A section jointly written by Brett R. Gordon and Raphael Thomadsen (both co-organizers of the workshop) discusses the workshop itself and some important thoughts for those people doing “structural econometrics in the trenches.” Finally, co-workshop organizer Richard Staelins section provides some perspective on both the workshop and structural econometrics as they relate to analytical models and empirical work for quantitative marketing researchers.

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Dennis Epple

University of South Florida

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