Quant Marketing PhD
Soon-To-Be Marketing Professor
I am currently a PhD Candidate at INSEAD in Fontainebleau, France, and will be joining the National University of Singapore from July as an Assistant Professor. My research interests lie at the intersection of quantitative marketing and industrial organisation, and I make use of both empirical and analytical methods. I am particularly interested in strategic decision-making, retail competition and complexity, which means I get excited by things like game-playing AIs, algorithmic pricing, and the cognitive processes involved in economic decision-making. I am grateful to have benefited during my PhD from the excellent guidance of Maria Ana Vitorino and Paulo Albuquerque.Prior to graduate school I worked as an economic consultant in Sydney with HoustonKemp Economists, Charles River Associates and Endgame Economics. In these positions I provided advice on the regulation of natural monopolies — particularly those arising in the electricity and gas sectors — and produced analyses supporting expert testimony in litigation. My analyses have been relied upon in matters before Australian state and federal courts, and in dispute settlement proceedings before the World Trade Organisation.I hold an MA in Economics from the University of Rochester, where I completed the applied / labour economics field of an economics PhD before switching to marketing science at INSEAD. I have also been awarded First Class Honours in Economics by the University of New South Wales and have a combined Bachelors of Economics and Commerce from the University of Western Australia.My PhD-friendly hobbies include travel, reading and coffee. Since moving to Fontainebleau I have taken up the local sport of bouldering, and I also enjoy diving whenever I find myself near warm water.
My research focuses on the network structure of retail competition and its implications for strategic decision-making and pricing. In my job market paper, I use high-frequency price data from Australian gasoline stations to estimate the network structure of station competition and study how it mediates the propagation of prices across a market. I develop and apply the idea of networked competition more broadly in my other work. Going forward, I plan to continue combining ideas from microeconomics and complex systems to advance our understanding of retail markets and dynamic competition.
Algorithmic Pricing and Network Competition: Evidence from Retail Gasoline Markets
with Maria Ana Vitorino | Job Market Paper
This paper studies the patterns of price monitoring and response mediating competition between pricing algorithms. It does so with the perspective that sparse substitution between the differentiated products being priced by algorithms gives their competition a network structure. In principle, such a structure introduces frictions into the responses of retailers to their competitors' price adjustments. Does it have this effect in practice? To answer this question we develop a method for estimating a retailer's competitors from the timing of their price adjustments. The method has a structural foundation but is implemented with computationally efficient machine learning methods. We apply the method to high-frequency price data from the gasoline industry. We find competition between gasoline stations is indeed networked, and that the responsiveness of stations' prices increases with their centrality in this network. Our findings imply automation will not remove all pricing frictions, that any collusion between algorithms must overcome complex information asymmetries, and that a network perspective is essential for understanding the effect of competition on retail market outcomes.
Mutual Fund Market Structure and Company Fee Competition: Theory and Evidence
with Ahmed Guecioueur
We investigate whether competition between the fund companies that offer mutual funds constrains individual fund fees. We document that over half of individual fund fee variation is explained by company-wide components. Moreover, we show using SEC prospectus download data that company-level attributes influence investors' consideration of companies. We connect these facts with a model of fee competition between co-considered fund companies, characterising the competitive landscape and associated equilibrium fees. Calibrating the model, we derive a testable prediction for competitively constrained fees. The prediction successfully explains cross-sectional variation in the company fee components, identifying the influence of company competition on fees.
In this paper, I question the typical characterisation of oligopoly markets as distinct sets of firms who all compete. Motivated by the observation that many retail markets have sparse substitution patterns, I argue markets can include firms who do not directly compete, but still influence each other through shared competitors – a situation Chamberlin (1933) called the "chain-linking" of markets. I present and study an oligopoly model with sparse substitution patterns to quantify (1) the influence of indirect competitors and (2) the magnitude of inferential biases possible when assuming markets are distinct and all firms within them compete. The model micro-founds sparse substitution in the demand of consumers who have heterogeneous consideration and convex preferences. The sparse substitution connects firms in a network, and I prove that their price competition over this network has a unique pure-strategy equilibrium for any pattern of consumer consideration. The influence of direct and indirect competitors can be measured by firms' centrality in the demand structure when the relative intensity of pairwise substitution is measured by diversion ratios. Comparative statics analysis reveals how conclusions about competition based on prices can be biased when markets are chain-linked. Numerical analysis shows the size of errors possible when ignoring the chain-linking of markets. Overall, the findings offer useful insights into the complex nature of retail markets and highlight the importance of accounting for indirect competition in empirical studies.
A PDF version of my CV can be found here.