Ph.D. candidate in Economics at the University of Oregon, interested in empirical IO and competition in digital markets.
Tech markets often feature high market concentration and frequent acquisitions. Understanding the motives underlying these acquisition strategies is therefore a first-order question for regulators and practitioners. I formulate a dynamic discrete choice model involving multiple agents to analyze acquisition records of the "big five" -- Google, Amazon, Microsoft, Meta, and Apple. I characterize the firms' acquisition decisions observed in the data as a Markov perfect equilibrium that are driven by their internal motives and defensive motives. I find that the defensive motives can explain a major share of their acquisition behaviors, sometimes overshadowing their internal motives of economies of scale. I show that a company might opt to acquire not necessarily because it enhances its core strengths, but to defend against its significant rivals (other members constituting 'tech giants') from obtaining targets that put itself at a competitive disadvantage.
Snippet -- The 79 sectors in which the tech giants made acquisitions
Colored in red are the top 20 sectors that have been popular among the tech giants for acquisitions from 1987 to 2021. To enlage the image, click here
Programming skills: R, Julia, Stata, PostgreSQL, SQL, Javascript, CSS, HTML, Python, Latex
Web applications developed
Technical and learning notes on few topics related to and including:
Insructor on Record:
Teaching Assistant / Grading Assistant:
Research Associate, Capital Economic Consulting Group, Lee & Ko Law Firm
Intern, UNESCO
Intern, Arthur D. Little
Intern, Institutional Shareholder Service
Ph.D. in Economics, University of Oregon
M.S. in Economics, University of Oregon
M.S. in Economics, Korea University
B.A. in Business Administration, Korea University