Course Syllabus

ECO 2901

INDUSTRIAL ORGANIZATION II

 University of Toronto. Department of Economics. Winter 2021

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Instructor: Victor Aguirregabiria.       Phone: 416-978-4358

E-mail: victor.aguirregabiria@utoronto.ca

Web:             http://individual.utoronto.ca/vaguirre

Online Lectures: Thursdays, 3-5pm via Zoom. Link: https://utoronto.zoom.us/j/82328612485 (Passcode: 967790)

Online Office Hours: Wednesdays-Fridays 5-6pm. Zoom Link: https://utoronto.zoom.us/j/82333857288 (Passcode: 128109)

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COURSE DESCRIPTION

This course deals with Empirical Industrial Organization. It covers topics related to econometric models and empirical applications of competition in industries. We study empirically the determinants of firms’ behaviour and market outcomes in the context of problems of market entry/exit, investment, innovation, product design, or networks. The course focuses on research papers using empirical games to investigate firms’ strategies and competition, and how firms’ information and beliefs play a fundamental role in the nature of competition and on market outcomes and welfare. The material includes recent research that relaxes standard assumptions of rational expectations and allow for firms’ limited information, biased beliefs, and learning. The course emphasizes the importance of combining data, economic models, and appropriate identification strategies and econometric techniques to answer empirical questions in economics.

 

MEETINGS

  • We have a 2-hours online lecture every Thursday from 3pm to 5pm.

Zoom Link:     https://utoronto.zoom.us/j/82328612485

  • Online Office Hours: Wednesdays-Fridays 5-6pm.

Zoom Link:     https://utoronto.zoom.us/j/82333857288

  • We will have class on Thursday, February 18th, during Reading Week.

 

EVALUATION

Your final grade will be based on the following requirements.

  • Problem set (50%). I will distribute the problem set online on Thursday, February 25th. Your completed problem set is due on Thursday, March 11th.
  • Final exam (50%). The final exam is a “Take Home Exam”. I will distribute the final exam on the last day of class on Thursday, April 1st. Your completed final exam is due on Thursday, April 8th.

 

OUTLINE AND REFERENCES

 

PART I:          STATIC MODELS OF MARKET ENTRY AND SPATIAL COMPETITION

 

Topic 1: Market entry models: complete information

  • Aguirregabiria, V. (2019): “Empirical Industrial Organization: Models, Methods and Applications,” Chapter 5.
  • Berry, S. and E. Tamer (2007): "Identification in Models of Oligopoly Entry," in Advances in Economics and Econometrics: Theory and Applications, Ninth World Congress, vol. 2, R. Blundell, W.K. Newey and T. Persson, eds., Cambridge Univ. Press.
  • Bresnahan, T. and P. Reiss (1991): “Econometric Models of Discrete Games,” Journal of Econometrics, 48, 57-81.
  • Tamer, E. (2003): “Incomplete Simultaneous Discrete Response Model with Multiple Equilibria,” Review of Economic Studies, 70(1), 147-165.
  • Ciliberto, F. and E. Tamer (2009): “Market Structure and Multiple Equilibria in Airline Markets,” Econometrica, 77(6), 1791-1828.

 

Topic 2: Market entry models: incomplete information

  • Aguirregabiria, V. (2019): “Empirical Industrial Organization: Models, Methods and Applications,” Chapter 5.
  • Bajari, P., H. Hong, J. Krainer and D. Nekipelov (2007): “Estimating Static Models of Strategic Interactions,” Journal of Business & Economic Statistics, 28(4), 469-482.
  • De Paula, A., and X. Tang (2012): “Inference of signs of interaction effects in simultaneous games with incomplete information,” Econometrica80(1), 143-172.
  • Sweeting, A. (2009): “The strategic timing incentives of commercial radio stations: An empirical analysis using multiple equilibria,” The RAND Journal of Economics40(4), 710-742.

 

Topic 3: Market entry and spatial competition

  • Aguirregabiria, V. and J. Suzuki (2016): “Empirical Models of Market Entry and Spatial Competition in Retail Industries,” in Handbook on the Economics of Retail and Distribution, Emek Basker (editor).
  • Ellickson, P., S. Houghton, and C. Timmins (2013): “Estimating network economies in retail chains: a revealed preference approach,” RAND Journal of Economics, 44(2), 169-193.
  • Seim, K. (2006): “An Empirical Model of Firm Entry with Endogenous Product-Type Choices,” RAND Journal of Economics 37(3).
  • Jia, P. (2008): “What Happens when Wal-Mart comes to town? Empirical Analysis of the Discount Retailing Industry,” Econometrica.

 

Topic 4: Relaxing assumptions on information structure in discrete choice games

  • Aguirregabiria, V., and P. Mira (2019): “Identification of games of incomplete information with multiple equilibria and unobserved heterogeneity,” Quantitative Economics10(4), 1659-1701.
  • Grieco, P. (2014): “Discrete games with flexible information structures: An application to local grocery markets,” The RAND Journal of Economics45(2), 303-340.
  • Magnolfi, L., and C. Roncoroni (2018): “Estimation of Discrete Games with Weak Assumptions on Information,” manuscript.

 

Topic 5: Static games of incomplete incomplete information with non-equilibrium beliefs

  • Aguirregabiria, V. (2020): “Identification of Firms’ Beliefs in Structural Models of Competition,” manuscript.
  • Aguirregabiria, V., and E. Xie (2019): “Identification of Non-Equilibrium Beliefs in Games of Incomplete Information Using Experimental Data,” manuscript.
  • Aradillas-Lopez, A., & Tamer, E. (2008): “The identification power of equilibrium in simple games,” Journal of Business & Economic Statistics, 26, 261-283.
  • Goldfarb, A., & Xiao, M. (2011): “Who thinks about the competition? Managerial ability and strategic entry in US local telephone markets,” American Economic Review, 101, 3130-3161.
  • Hortacsu, A., Luco, F., Puller, S. & Zhu, D. (2019): “Does strategic ability affect efficiency? Evidence from electricity markets,” American Economic Review, 109(12), 4302-42.

 

PART II:         DYNAMIC GAMES OF OLIGOPOLY COMPETITION

 

Topic 6: Dynamic games of oligopoly competition: Models and Solution methods

  • Aguirregabiria, V. (2019): “Empirical Industrial Organization: Models, Methods and Applications,” Chapter 9.
  • Ericson, R. and A. Pakes (1995): “Markov-Perfect Industry Dynamics: A Framework for Empirical Work,” Review of Economic Studies, 62, 53-82.
  • Pakes, A. and P. McGuire (1994): “Computing Markov Perfect Nash Equilibrium: Numerical Implications of a Dynamic Differentiated Product Model,” RAND Journal of Economics, 25, 555-589.

 

Topic 7: Dynamic games of oligopoly competition: Estimation methods

  • Aguirregabiria, V. (2019): “Empirical Industrial Organization: Models, Methods and Applications,” Chapter 10.
  • Aguirregabiria, V., and M. Marcoux (2019): “Imposing equilibrium restrictions in the estimation of dynamic discrete games,” manuscript. University of Toronto.
  • Aguirregabiria, V., and P. Mira (2007): “Sequential estimation of dynamic discrete games,” Econometrica, 75, 1-53.
  • Arcidiacono, P., and R. Miller (2011): “Conditional choice probability estimation of dynamic discrete choice models with unobserved heterogeneity,” Econometrica, 79(6), 1823-1867.
  • Bajari, P., L. Benkard and J. Levin (2007): “Estimating dynamic models of imperfect competition,” Econometrica, 75, 1331-1370.

 

Topic 8: Entry, exit, preemption, and cannibalization in retail industries

  • Arcidiacono, P., P. Bayer, J. Blevins, and P. Ellickson (2016): “Estimation of dynamic discrete choice models in continuous time with an application to retail competition,” The Review of Economic Studies83(3), 889-931.
  • Holmes, T. (2011): “The Diffusion of Wal-Mart and Economies of Density,” Econometrica, 79(1), 253-302.
  • Igami, M., and N. Yang (2016): “Unobserved heterogeneity in dynamic games: Cannibalization and preemptive entry of hamburger chains in Canada,” Quantitative Economics7(2), 483-521.
  • Takahashi, Y. (2015): “Estimating a war of attrition: The case of the US movie theater industry,” American Economic Review105(7), 2204-41.

 

Topic 9: Uncertainty and firms’ investment decisions

  • Collard‐Wexler, A. (2013): “Demand fluctuations in the ready‐mix concrete industry,” Econometrica81(3), 1003-1037.
  • Kalouptsidi, M. (2014): “Time to build and fluctuations in bulk shipping,” American Economic Review104(2), 564-608.
  • Kellogg, R. (2014): “The effect of uncertainty on investment: Evidence from Texas oil drilling,” American Economic Review104(6), 1698-1734.

 

Topic 10: Networks and  product positioning

  • Aguirregabiria, V., and C-Y. Ho (2012): "A dynamic oligopoly game of the US airline industry: Estimation and policy experiments," Journal of Econometrics, 168(1), 156-173.
  • Benkard, C., A. Bodoh-Creed, and J. Lazarev (2019): “Simulating the dynamic effects of horizontal mergers: US airlines,” Manuscript, Yale University.
  • Brancaccio, G., M. Kalouptsidi, and T. Papageorgiou (2020): “Geography, search frictions and endogenous trade costs,”Econometrica. Forthcoming.
  • Jeziorski, P. (2014): “Estimation of cost efficiencies from mergers: Application to US radio,” The RAND Journal of Economics45(4), 816-846.

 

Topic 11: Dynamic games of innovation

  • Goettler, R. and B. Gordon (2011): “Does AMD spur Intel to innovate more?” Journal of Political Economy, 119(6), 1141-1200.
  • Igami, M (2017): “Estimating the Innovator's Dilemma: Structural Analysis of Creative Destruction in the Hard Disk Drive Industry,” Journal of Political Economy,  125(3)798-847

  

Topic 12: Dynamic games with firms’ non-equilibrium beliefs and learning

  • Aguirregabiria, V. and J. Jeon (2020): “Firms’ Beliefs and Learning: Models, Identification, and Empirical Evidence,” Review of Industrial Organization, forthcoming.
  • Aguirregabiria, V., & Magesan, A. (2020): “Identification and estimation of dynamics games when players beliefs are not in equilibrium, working paper,” Review of Economic Studies, forthcoming.
  • Asker, J., Fershtman, C., Jeon, J., & Pakes, A. (2016): “The competitive effects of information sharing,” NBER Working Paper, No. 22836. National Bureau of Economic Research.
  • Doraszelski, U., Lewis, G., & Pakes, A. (2018): “Just starting out: Learning and equilibrium in a new market,” American Economic Review, 108, 565-615.
  • Fershtman, C., & Pakes, A. (2012): “Dynamic games with asymmetric information: A framework for empirical work,” Quarterly Journal of Economics, 127, 1611-1661.

 

CLASS SCHEDULE & REQUIRED READINGS BEFORE CLASS

 

WEEK- DATE                  TOPIC                ________________

Week 1: Jan. 14                 Topic 1: Market entry models: complete information

Week 2: Jan. 21                 Topic 2: Market entry models: incomplete information

Week 3: Jan. 28                 Topic 3: Market entry and spatial competition

Week 4: Feb. 4                   Topic 4: Relaxing assumptions on information structure in discrete choice games

Week 5: Feb. 11                 Topic 5: Static games of incomplete information with non-equilibrium beliefs

Week 6: Feb. 18                 Topic 6: Dynamic games of oligopoly competition: Models and Solution methods. [Note: Reading week, but we have class]

Week 7: Feb. 25                 Topic 7: Dynamic games of oligopoly competition: Estimation methods. Problem set will be handed-out

Week 8: Mar. 4                  Topic 8: Entry, exit, preemption, and cannibalization in retail industries

Week 9: Mar. 11                Topic 9: Uncertainty and firms’ investment decisions. Problem set is due

Week 10: Mar. 18              Topic 10: Networks and product positioning

Week 11: Mar. 25              Topic 11: Dynamic games of innovation

Week 12: Apr 1.               Topic 12: Dynamic games with firms’ non-equilibrium beliefs and learning. ‘Take Home’ Final Exam set will be handed-out

Week 13: Apr. 8                Final Exam is due

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Course Summary:

Date Details Due