Econ 829: Empirical Industrial Organization Spring 2013

O¢ ce: Phone: E-mail: O¢ ce hours:

Kathleen Nosal 4-17, L7, 3-5 (621) 181-3426 [email protected] Tuesdays and Fridays 9-10 or by appointment

Alex Shcherbakov 3-13, L7, 3-5 (621) 181-1838 [email protected] by appointment, or just stop by

Summary: This course covers recent techniques in development and estimation of dynamic models of investment and consumer behavior as well as dynamic oligopoly models. Each topic will be related to one or more recent papers in I.O. (particular papers from the reading list will be assigned later). We will discuss in detail the model, research question, sources of identi…cation and estimation methodology. The reading list below is meant to provide a starting point for reading on each topic and it does not attempt to be comprehensive. Outline: 1. Introduction to dynamic models, Aguirregabiria and Mira (2010) 2. Math preliminaries 3. Optimal stopping problems, Rust (1987) 4. Finite horizon problems: patents as options, Pakes (1986) 5. Two-step methods (a) Hotz and Miller (1993) (b) Hotz, Miller, Sanders and Smith (1994) (c) Aguirregabiria and Mira (2002) 6. Dynamic demand models (a) Durable products: Gowrisankaran and Rysman (2012) (b) Storable products: Hendel and Nevo (2006), Hendel and Nevo (2011) (c) Switching costs: Nosal (2013), Shcherbakov (2013) 7. Dynamics of Learning (optional topic): Ackerberg (2003), Crawford and Shum(2005) 8. Multi-agent dynamics: introduction (a) Markov perfect industry dynamics: Ericson and Pakes (1995) (b) Some theoretical foundation of MPE: Doraszelski and Satterthwaite (2010) 9. Computing MPE: Pakes and McGuire (1994, 2001) 10. Identi…cation, multiple equilibria, and heterogeneity vs state dependence 11. Estimation of dynamic games: concept of full solution approach and its di¢ culties, curse of dimensionality: Benkard (2004) 12. Two-step methods 1: Aguirregabiria and Mira (2007) 13. Two-step methods 2: Bajari, Benkard, and Levin (2007) 14. Two-step methods 3: Pakes, Ostrovsky, and Berry (2008), Pesendorfer and Schmidt-Dengler (2008), Arcidiacono and Miller (2008)

1

15. Applications: Ryan (2011), Collard-Wexler (2010), Sweeting (2011), Aguirregabiria and Ho (2011), Schmidt-Dengler (2006) 16. Optional topics: (a) Empirical models of collusion (b) Estimating production functions (c) Continuous choice models

2

Reading list: 1

Introduction Aguirregabiria, V. and P. Mira. (2010) “Dynamic Discrete Choice Structural Models: A Survey,” Journal of Econometrics. 156(1), 38-67.

2

Single agent dynamics Ackerberg, D. (1999). An MSM Estimator for Discrete Choice Panel Data with Arbitrary Error Structure. Working paper. Ackerberg, D. (2003). Advertising, learning, and consumer choice in experience good markets: an empirical examination. International Economic Review 44(3):1007-1040. Ackerberg, D. (2009). A new use of importance sampling to reduce computational burden in simulation estimation. Quantitative Marketing and Economics, 7(4): 343-376. Aguirregabiria, V. and Mira, P. (2002). Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models. Econometrica 70(4):1519-1543. Ericson, R. and Pakes, A. (1995). Markov-perfect industry dynamics: a framework for empirical work. Review of Economic Studies, 62(1): 53-83. Hotz, V. and Miller, R. (1993). Conditional Choice Probabilities and the Estimation of Dynamic Models. Review of Economic Studies 60(3).497-529. Hotz, V., R. Miller, S. Sanders and J. Smith. (1994) The Review of Economic Studies, Vol. 61, No. 2., pp. 265-289. Pakes, A. (1986). Patents as options: some estimates of the value of holding European patent stocks. Econometrica 54(4): 755-784. Rust, J. (1987). Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher. Econometrica 55(5):999-1033.

3

Dynamic demand for di¤erentiated products Ackerberg, D. (2003). Advertising, Learning, and Consumer choice in experience good markets: A structural empirical examination. International Economic Review 44: 1007-1040. Carranza, J. (2006). Consumer Heterogeneity, Demand for Durable Goods and the Dynamics of Quality. Manuscript. University of Wisconsin-Madison. Gowrisankaran, G. and Rysman, M. (2007). Dynamics of Consumer Demand for New Durable Goods. Working paper. Hendel, I. and Nevo, A. (2006). "Measuring the Implications of Sales and Consumer Inventory Behavior. Econometrica 74(6):1637-1673. Hendel, I. and Nevo, A. (2011). Intertemporal Price Discrimination in Storable Goods Markets. Forthcoming, American Economic Review. Melnikov, O. (2001). Demand for Di¤erentiated Durable Products: The Case of the US Computer Printer Market. Working paper. Schiraldi, P. (2008). Automobile replacement: A dynamic structural approach. Working paper.

3

4

Dynamics of Learning in Single Agent Models Ackerberg, D. (2003). Advertising, Learning, and Consumer choice in experience good markets: A structural empirical examination. International Economic Review 44: 1007-1040. Crawford, G. and M. Shum (2005). Uncertainty and Learning in Pharmaceutical Demand. Econometrica 73(4): 1135-1174.

5

Dynamic oligopoly models Ackerberg, D., Benkard, L., Berry, S. and Pakes, A. (2007). Econometric Tools for Analyzing Market Outcomes. Handbook of Econometrics, Chapter 63, 6(A):4172-4276. Bajari, P., Benkard, L. and Levin, J. (2007). Estimating Dynamic Models of Imperfect Competition. Econometrica 75:1331-70. Benkard, C. (2004). A Dynamic Analysis of the Market for Wide-Bodied Commercial Aircraft, Review of Economic Studies, 71: 581-611. Doraszelski, U. and Satterthwaite, M. (2007). Foundations of Markov-Perfect Industry Dynamics: Existence, Puri…cation, and Multiplicity. Manuscript, Harvard University. Ericson, R. and Pakes, A. (1995). Markov Perfect Industry Dynamics: A Framework for Empirical Work. Review of Economic Studies 53-82. Pakes, A. and McGuire, P. (1994). Computing Markov-Perfect Nash Equilibria: Numerical Implications of a Dynamic Di¤erentiated Product Model. RAND Journal of Economics 25(4):555589. Pakes, A. and McGuire, P. (2001). Stochastic Algorithms, Symmetric Markov Perfect Equilibrium, and the ’Curse’of Dimensionality. Econometrica 69(5): 1261-1281. Ryan, S. (2007). The Costs of Environmental Regulation in a Concentrated Industry. Working paper.

6

Discrete choice oligopoly models Aguirregabiria, V. and Mira, P. (2007). Sequential Estimation of Dynamic Discrete Games. Econometrica 75(1): 1-53. Aguirregabiria, V., Roman, H., and Mira, P. (2007). An Estimable Dynamic Model of Entry, Exit and Growth in Oligopoly Retail Markets. American Economic Review 97(2): 449-454. Arcidiacono, P. and Miller, R. (2008). CCP Estimation of Dynamic Discrete Choice Models with Unobserved Heterogeneity. Working paper. Bajari, P. and Hong, H. (2007). Semiparametric Estimation of a Dynamic Game of Incomplete Information. Working paper. Collard-Wexler, A. (2006). Demand Fluctuations and Plant Turnover in the Ready-Mix Concrete Industry. Working paper. Dunne, T., Klimek, S., Roberts, M. and Xu, Y. (2007). The dynamics of market structure and market size in two health services industries. Working paper. Pakes, A., Ostrovsky, M., and Berry, S. (2008). Simple estimators for the parameters of discrete dynamic games (with entry / exit examples). RAND Journal of Economics, forthcoming. Pesendorfer, M. and Schmidt-Dengler, P. (2008). Asymptotic Least Squares Estimators for Dynamic Games. Review of Economic Studies 75(3): 901-928. Schmidt-Dengler, P. (2008). The Timing of New Technology Adoption: The Case of MRI. Working paper.

4