Strategy I: Econometric tools for strategy research

Friday 15:00 to 18:00 in 7-191.

This course is intended to develop the toolbox of PhD students intending to pursue research in strategy (or other business related fields). It focuses on the set of tools that are provided by the discipline of economics, hence a focus on models of oligopoly and contract theory, and a focus on empirical tools such as the measurement and identification of treatment effects and basic econometrics.

This course is about tools that are useful for the execution of the research spurred by your answers to these questions. The tools covered in this course will be drawn from the field of economics. Hence, this will feel like a applied micro course most of the time. As a result it will likely also be useful to people looking at doing research Industrial Organization, Labor Relations, Marketing, Empirical Corporate Finance, Empirical Accounting and other areas of business related research when field data needs to be interrogated and interpreted.

We will cover some areas of micro theory that are important for understanding firm behaviour. This will cover the first 4 weeks of the course. We will assume you have done a micro course at the PhD level before, and that this course covered basic game theory and demand and supply (price theory). Bits of these four weeks will likely feel like revision, but it is good to go over this stuff from an applied perspective anyway.

Following that we will think about how to use data to understand the world. Economics has been quite successful at developing ways to infer stuff from data. The field of econometrics combines ideas from economic theory models and statistical methods in a way that gives a very powerful approach to inference when confronting data that are contaminated by market forces (ie. when the data comes from a market interaction rather than a lab or field experiment).

In the language of econometrics we will be looking at reduced form micro-econometrics with particular attention on issues of identification, both theoretical and in application. To do this well, you need to understand econometric technique, theory and how to mesh the two together and it is an appreciation of this meshing process that is our ultimate goal for the course.

Increasingly, applied work lives or dies on how compelling the identification strategy is, and the art of constructing a good identification strategy in data work is important to being a good applied researcher.


Four problem sets: One theory and three empirical.
  • PS 1: Empirical problem set 1 20% on Natural Experiments and Difference-in-Difference Approaches using Card and Kruger New Jersey-Pennsylvania Experiment. Problem Set 1
  • PS 2: Empirical problem set 2 20% on Productivity. Problem Set 2
  • PS 3: Theoretical problem set - culled from text books. 20%
  • PS 4: Empirical Problem Set 4 20% using Electricity Data.
In class participation will count for an additional 20%. Participation means reading the assigned papers and thinking about them. You lose 1% every time you have to admit that you didn't read the paper being discussed. Occasionally we will ask you to present papers. This will be good practice for you so you should be eager to do this. good presentation skills are critical to a successful career.

Recommended Books

  • B. Salanie: A Primer on Contract Theory.
  • An Econometrics Textbook (Woodford [Econometric Analysis of Cross Section and Panel Data] for details of specific approaches and Hayashi [Econometrics] for general approach, we assume you already own a copy of Bill Greene's book).
  • Angrist, Joshua D. and Jorn-Steffen Pischke (2009). Mostly Harmless Econometrics: An Empiricist's Companion, is a very opinionated book on econometrics and empirical research. Something to read once you've read some more fundamental reference books.
  • Manski, C. (1995), Identification Problems in the Social Sciences, Harvard University Press. Classic on Identification.
  • Tirole: The Theory of Industrial Organization (classic textbook statement of IO theory (up to 1990))
  • Mcloskey, D: Economical Writing (2001) (clear discussion of writing in economics).
  • Tufte, E: Visual Display of Quantitative Information (graphs and tables are also writing).

Topics and reading by week

  • Week 1: Review of non-cooperative game theory approaches to basic industry models (lecture notes)
  • Solution concepts; Cournot; Bertrand; Stackelberg; Product Differentiation; HHI; other stuff
    Readings: Lecture Notes supplemented by Tirole; Oz Shy "Industrial Organization: Theory and Applications'' (aka baby Tirole); Fudenberg and Tirole
    John Asker will present "Exclusionary Minimum Resale Price Maintenance".
  • Week 2: Identification and Data Problems in Economics (lecture notes)
  • Conditional Expectations, Identification in a formal sense, Selection, Treatment and Simultaneity.
    • * Manski (1995) `Identification Problems in the Social Sciences'.
    • Griliches "Data Problems in Economics'' NBER Working Paper T0039.
    • Moffitt, Robert (2005) "Remarks on the Analysis of Causal Relationships in Population Research''. Demography 42(1): 91-108.
    • McCloskey D, Ziliak S T. (1996). "The Standard Error of Regressions.'' Journal of Economic Literature 34(1): 97-114.
  • Week 3: Review of basic econometrics with focus on identification (lecture notes)
  • Conditional Expectations, Identification in a formal sense, Selection, Treatment and Simultaneity, GMM and MLE, OLS, Endogeniety, Working 1928, IV, 2SLS,
    • Hayashi "Econometrics'' chapters 1,2 and 3.
    Note: Go over identification of binary choice model, multinomial choice model, and identification of a search model, identification of a game with inequalities. Supply and Demand.
  • Week 4: Bootstrap, Kernel Density Estimates, Natural experiments (lecture notes)
  • Readings:
    • Chapter 6 of Efron and Tsibshirani (1993) "An Introduction to the Bootstrap''.
    • Appendix A1 of Horowitz (2009) "Semiparametric and Nonparametric Methods in Econometrics'' on Kernel Density Estimation.
    • * Lyall, J (2009) "Does Indiscriminate Violence Incite Insurgent Attacks?: Evidence from Chechnya'' Journal of Conflict Resolution vol. 53 (3) pp. 331-362.
    • Greenstone, M and E Moretti (2010) "Bidding for Industrial Plants: Does Winning a Million Dollar Plant Increase Welfare?'' Working Paper.
    • "Does Management Matter? Evidence from India'' working paper by Bloom et al.
    • Sargent et al. "Reduced incidence of admissions for myocardial infarction associated with public smoking ban: before and after study'' British Medical Journal (2004) vol. 328 (7446) pp. 977-80.
  • Week 5: Differences-in-difference methods for causal inference (lecture notes)
  • Readings:
    • * Card and Krueger (1994) "Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania'' The American Economic Review (1994) vol. 84 (4) pp. 772-793.
    • * Jin, G and Leslie, P (2004) "The Effect of Information on Product Quality: Evidence from Restaurant Hygiene Grade Cards'' The Quarterly Journal of Economics vol. 118 (2) pp. 409-451
    • Mas, Alex "Labour Unrest and the Quality of Production: Evidence from the Construction Equipment Resale Market'' Review of Economic Studies (2008) vol. 1 pp. 1-30.
    • Milyo, and Waldfogel (2004) "The effect of Advertising''
    • Woolridge and Imbens, (2009) "Cemmap Lecture Notes 11''.
  • Week 6: Propensity score matching and Control Functions (lecture notes)
  • Readings:
    • De Loecker, Jan, 2007 "Do exports generate higher productivity? Evidence from Slovenia'' Journal of International Economics, vol. 73(1), pages 69-98, September.
    • Dehejia and Wahba (1999), Causal Effects in Non- experimental Studies: Reevaluating the Evaluation of Training Programs, Journal of the American Statistical Association, 94,448, pp. 1053-62
    • Chandra and Collard-Wexler, Mergers in Two-Sided Markets: An Application to the Canadian Newspaper Industry, JEMS.
    • Heckman, James, Robert Lalonde and Jeffrey Smith (1999): "The Economics and Econometrics of Active Labor Market Programs?'' in Orley Ashenfelter and David Card, eds., Handbook of Labor Economics Volume 3A (Amsterdam: North-Holland), 1865-2097.
    • Heckman, James, Hidehiko Ichimura and Petra Todd (1998), "Matching As An Econometric Evaluation Estimator'' Review of Economic Studies, 65(2), 261-294.
    • Abadie, Alberto and Guido Imbens (2004a): "On the Failure of the Bootstrap for Matching Estimators," manuscript, Harvard University.
    • Part of Olley, G. S., and A. Pakes (1996): "The dynamics of productivity in the telecommunications equipment industry,'' Econometrica, 64(6), 35.
  • Week 9: Regression discontinuity and Weak Instruments (lecture notes)
  • Readings:
    • Angrist, J.D., and V. Lavy, (1999), "Using Maimonides' Rule to Estimate the Effect of Class Size on Scholastic Achievement'', Quarterly Journal of Economics 114, 533-575.
    • Black, S., (1999), "Do Better Schools Matter? Parental Valuation of Elementary Education'', Quarterly Journal of Economics 114, 577-599.
    • Lee, David, "Randomized Experiments from Non-random Selection in U.S. House Elections'' Journal of Econometrics, 2008, 142:2, 675-697.
    • Woolridge and Imbens (2009) "Cemmap Lecture Notes'' Chapter 12.
    • Bound, Jaeger and Baker (1995) "Problems with Instrumental Variables Estimation When the Correlation Between the Instruments and the Endogeneous Explanatory Variable is Weak'' Journal of the American Statistical Association, Vol. 90, No. 430 (Jun., 1995), pp. 443- 450.
  • Week 10: Panel data, time series and correlation of observations (lecture notes)
  • Fixed Effects, Serially Correlation of observations, clustering standard errors.
    • Joshua D. Angrist and Jorn-Steffen Pischke (2009) "Mostly Harmless Econometrics: An Empiricist's Companion'', Princeton University Press. Chapter 8.
    • Bertrand, M., E. Duflo, and S. Mullainathan (2004), "How Much Should We Trust Differences- in-Differences Estimates?", Quarterly Journal of Economics, February, 119(1): 249-275.
    • Benkard, L (2000) "Learning and forgetting: The dynamics of aircraft production'' American Economic Review, Vol. 90, No. 4 (Sep., 2000), pp. 1034-1054.
    • Woolridge and Imbens, (2009) "Cemmap Lecture Notes 11''.
  • Week 11: Productivity (lecture notes)
  • Productivity Estimation and Reallocation.
    • * Ackerberg, D., G. Frazer, and K. Caves (2006): "Structural Estimation of Production Function,'' Working Paper UCLA.
    • * Foster, L., J. Haltiwanger, and C. Krizan (2001): "Aggregate productivity growth. Lessons from microeconomic evidence,'' .
    • Foster, L., J. Haltiwanger, and C. Krizan (2006): "Market selection, reallocation, and restructuring in the US retail trade sector in the 1990s,'' The Review of Economics and Statistics, 88(4), 748–758.
    • Griliches, Zvi, and Jacques Mairesse (1995) "Production Functions: The Search for Identification.'' NBER Working Paper \#5067.
    • Levinsohn, J., and A. Petrin (2003): "Estimating Production Functions Using Inputs to Control for Unobservables,'' Review of Economic Studies, 70(2), 317–341.
    • * Olley, G. S., and A. Pakes (1996): "The dynamics of productivity in the telecommunications equipment industry,'' Econometrica, 64(6), 35.
    • Pavcnik, N. (2002): "Trade Liberalization, Exit, and Productivity Improvement: Evidence from Chilean Plants,'' Review of Economic Studies, 69(1), 245–76.
  • Week 12: Quantile and median regression, Attenuation Bias (lecture notes)
    • Goldberg (1995) "Price Discrimination''.
    • Syverson, C. (2004): "Market Structure and Productivity: A Concrete Example,'' Journal of Political Economy, 112(6), 1181–1222.
    • Woolridge and Imbens, (2009) "Cemmap Lecture Notes 16''.
    • Griliches and Hausmann (1986) "Errors in variables in panel data'' Journal of Econometrics, Volume 31, Issue 1, February 1986, Pages 93-118
    • Bound, John and Alan B. Krueger (1991) "The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?'' Journal of Labor Economics,12,pp 345-68.
  • Week 13: Theory of the firm and organisations I: The moral hazard model (lecture notes)
    • Basic Model with a few extensions
    • The first-order approach.
    • George Baker and Thom Hubbbard ``Make Versus Buy in Trucking: Asset Ownership, Job Design, and Information'' American Economic Review.
    Reading: Salanie Ch 5,
  • Week 14: Theory of the firm and organisations II: The adverse selection model
  • Mussa-Rosen, extensions to regulation, auctions, lemons markets
    Reading: Salanie
  • Week 15: Theory of the firm and organisations III: The incomplete contracts model and bargaining
  • Property rights approach, Bargaining
    • Salanie Ch 7
    • Monteverdi, Kirk and David Teece, Supplier switching costs and vertical integration in the automobile industry, Bell Journal of Economics, 13(1) 206-213 (1982)
    • Klein, Benjamin, Robert G Crawford and Armen A Alchian, Vertical Integration, Appropriable Rents, and the Competitive Contracting Process, Journal of Law and Economics, 21(2) 297-326, 1978
    • Segal, Ilya and Michael Whinston, Exclusive Contracts and protection of investments, RAND Journal of Economics, 31(4), 603-633, 2000.
  • Week 16: Data on Businesses: Strategies for search and collection.
  • On this week, Lai Jiang, Kei Kawai, Selvin Akkus, Krzysztof Wozniak and Bryan Bollinger will talk about strategies for collecting data. Then we go have beers and start obsessing about how to write a dissertation.