Mitsuru (Michi) Igami, associate professor at Yale Department of Economics (and visiting associate professor at MIT Department of Economics for 2017–2018), empirically studies strategic industry dynamics.
TOPICS: (i) innovation, (ii) mergers, (iii) cartels, and (iv) artificial intelligence.
FIELDS: Industrial Organization, Economics of Innovation, International Trade.
Econometric Society 2018 North American Winter Meeting, Philadelphia (1/6/2018) Harvard econometrics lunch (2/5) NBER Industrial Organization program meeting, Stanford (2/9) Washington University in St. Louis (2/19–21)
Johns Hopkins University (2/28/2018)
Pontifícia Universidade Católica do Rio de Janeiro, Brasil (3/6)
Fundação Getúlio Vargas, Brasil (3/8)
Conference on Structural Dynamics, University of Copenhagen (5/31–6/1)
Summer School on the Empirical Application of Dynamic Programming Models, University of Copenhagen (6/2–6/3)
Directorate General for Competition, European Commission (6/6)
Hal White Antitrust Conference, Bates White (6/11–12)
Japanese Economic Association Meeting, Gakushuin University (9/8–9)
- "Industry Dynamics of Offshoring: The Case of Hard Disk Drives," American Economic Journal: Microeconomics, 10:1 (February 2018), 67–101. This paper uncovers a novel pattern of offshoring dynamics in a high-tech industry, and proposes a structural model to explain it. Specifically, the hard disk drive industry (1976–98) witnessed massive waves of entry, exit, and the relocation of manufacturing plants to low-cost countries, in which shakeouts occurred predominantly among home firms and almost all survivors were offshore firms. I build and estimate a dynamic offshoring game with entry/exit to measure the benefits and costs of offshoring, investigate the relationship between offshoring and market structure, and assess the impacts of hypothetical government interventions.
- "Estimating the Innovator’s Dilemma: Structural Analysis of Creative Destruction in the Hard Disk Drive Industry, 1981–1998," the Journal of Political Economy, 125:3 (June 2017), 798–847. [Link to SSRN working paper version]. This paper studies strategic industry dynamics of creative destruction in which firms and technologies experience turnover. Theories predict cannibalization between existing and new products delays incumbents’ innovation, whereas preemptive motives accelerate it. Incumbents’ cost (dis)advantage relative to that of entrants would further reinforce these tendencies. To empirically assess these three forces, I develop and estimate a dynamic oligopoly model using a unique panel data set of hard disk drive (HDD) manufacturers (1981–98). The results suggest that despite strong preemptive motives and a substantial cost advantage over entrants, cannibalization makes incumbents reluctant to innovate, which can explain at least 57% of the incumbent-entrant innovation gap. I then assess hypothetical policy interventions concerning broad patents and license fees, and find the industry’s welfare trajectory difficult to outperform.
- "Unobserved Heterogeneity in Dynamic Games: Cannibalization and Preemptive Entry of Hamburger Chains in Canada," with Nathan Yang, Quantitative Economics, 7:2 (July 2016), 483–521. We develop a dynamic entry model of multi-store oligopoly with heterogeneous markets, and estimate it using data on hamburger chains in Canada (1970–2005). Because more lucrative markets attract more entry, firms appear to favor the presence of more rivals. Thus unobserved heterogeneity across geographical markets creates an endogeneity problem and poses a methodological challenge in the estimation of dynamic games, which we address by combining the procedures proposed by Kasahara and Shimotsu (2009), Arcidiacono and Miller (2011), and Bajari, Benkard, and Levin (2007), respectively. The results suggest the omission of unobserved market heterogeneity attenuates the estimates of competition, and the tradeoff between cannibalization and preemption is an important factor behind the evolution of market structure.
- "Market Power in International Commodity Trade: The Case of Coffee," the Journal of Industrial Economics, 63:2 (June 2015), 225–248. [Link to SSRN working paper version]. This paper studies the impact of market power on international commodity prices. I use a standard oligopoly model and exploit historical variations in the structure of the international coffee bean market to assess the impact of a cartel treaty on coffee prices and its global welfare consequences. The results suggest the International Coffee Agreement (ICA, 1965-89) raised its price by 75% above the Cournot-competitive level, annually transferring approximately $12 billion from consumers to exporting countries, and its lapse in 1989 explains four-fifths of the subsequent price decline, that is, the "coffee crisis."
- "Does Big Drive Out Small? - Entry, Exit, and Differentiation in the Supermarket Industry," the Review of Industrial Organization, 38:1 (January 2011), 1-21. This paper measures the impact of the entry of large supermarkets on incumbents of various sizes. Contrary to the conventional notion that big stores drive small rivals out of the market, data from Tokyo in the 1990s show that large supermarkets' entry induces the exit of existing large and medium-size competitors, but improves the survival rate of small supermarkets. These findings highlight the role of store size as an important dimension of product differentiation. Size-based entry regulations would appear to protect big incumbents, at the expense of small incumbents and potential entrants.
- "Mergers, Innovation, and Entry-Exit Dynamics: Consolidation of the Hard Disk Drive Industry, 1996–2016," with Kosuke Uetake (September 4, 2017). How far should an industry be allowed to consolidate when competition and innovation are endogenous? We extend Rust's (1987) framework to incorporate a stochastically alternating-move game of dynamic oligopoly, and estimate it using data from the hard disk drive industry, in which a dozen global players consolidated into only three in the last 20 years. We find plateau-shaped equilibrium relationships between competition and innovation, with systematic heterogeneity across time and productivity. Our counterfactual simulations suggest the optimal policy should stop mergers when six or fewer firms exist, highlighting a dynamic welfare tradeoff between ex-post pro-competitive effects and ex-ante value-destruction side effects.
- "Privatization and Productivity in China," with Yuyu Chen, Masayuki Sawada, and Mo Xiao (September 22, 2017). We study the impact of privatization in China, which has been credited for part of the country's productivity growth. Because privatization involves political processes, self-selection and unobserved heterogeneity create endogeneity problems, which we address by augmenting the nonparametric approach of Gandhi, Navarro, and Rivers (2016) to incorporate firms' ownership types and their endogenous changes. Results suggest the average short-run and long-run gains from privatization are 43% and 92%, respectively, and are larger in consumer-good industries than capital-good ones. By contrast, new-product surveys and patent statistics show state-owned enterprises outperform private firms, highlighting curious heterogeneity in the capabilities and/or incentives to innovate.
- "Measuring the Incentive to Collude: The Vitamin Cartels, 1990–1999," with Takuo Sugaya (July 12, 2017). Why do some cartels survive for a decade whereas others collapse within a few years? Models of collusion are difficult to identify, but the vitamins case, one of the largest in history, entails direct evidence from American courts and European agencies. We provide a theory-based measurement of the incentive to collude, and test a fundamental prediction of game theory that cooperation is self-enforcing if and only if it is incentive compatible. Our simple repeated-game model could explain the life and death of various vitamin cartels. Simulations suggest a hypothetical merger could have prolonged the vitamin C cartel.
- "Artificial Intelligence as Structural Estimation: Economic Interpretations of Deep Blue, Bonanza, and AlphaGo," (October 30, 2017). Artificial intelligence (AI) has achieved superhuman performance in a growing number of tasks, including the classical games of chess, shogi, and Go, but understanding and explaining AI remain challenging. This paper studies the machine-learning algorithms for developing the game AIs, and provides their structural interpretations. Specifically, chess-playing Deep Blue is a calibrated value function, whereas shogi-playing Bonanza represents an estimated value function via Rust's (1987) nested fixed-point method. AlphaGo's "supervised-learning policy network" is a deep neural network (DNN) version of Hotz and Miller's (1993) conditional choice probability estimates; its "reinforcement-learning value network" is equivalent to Hotz, Miller, Sanders, and Smith's (1994) simulation method for estimating the value function. Their performances suggest DNNs are a useful functional form when the state space is large and data are sparse. Explicitly incorporating strategic interactions and unobserved heterogeneity in the data-generating process would further improve AIs' explicability.
PROJECTS UNDER CONSTRUCTION
- Acquiring a String of Pearls (with Yasin Özcan & Yasuaki Hiraoka), since June 2015.
- Moore's Law, since June 2013.
- Patent Statistics as an Innovation Indicator? Evidence from the Hard Disk Drive Industry, with Jai Subrahmanyam (January 9, 2015).
- Age, Experience, and Artistic Creativity: the Case of Weekly Jump (March 2012).