目录：
This a brief outline of the topics that are likely to be covered. Exactly
what is covered, and in which order, depends a bit on how fast we go, and
on teacher and class interests.
1. Background
 A potted history of I.O.
 Empirical regularities and some notes on data availability.
 A digression on Gibrat's Law and the need for theory.
 A framework for applied analysis (and its limitations).
 Some Simple Static Models as a Starting Point; Supply and De-
mand, Houthackker, Lucas, and Extensions.
2. Production and Cost Functions: Uses, Data, and Estimation Problems.
 Review: Overview on the uses of cost functions. The primal and
dual problems, multi-product functions and xed costs.
 Estimation; Types of data, simultaneity, and selection problems.
 Extensions: Learning by doing, characteristic based cost func-
tions.
 Productivity analysis and measuring technical change.
 Empirical applications: De-regulation of telecommunications, Tar-
i policy and productivity. Learning in the Aircraft Industry.
3. Demand Systems
1
 Review: Overview on the uses of demand functions. Product vs.
characteristic space.
 Product Space. Gorman's forms and extensions. Estimation Prob-
lems.
 Characteristics Space. Theory and estimation.
 Problem set: Estimating (extensions of) the vertical model.
 Empirical applications; Own and cross price elasticities and their
uses (autos, cereals, ...). New goods (the CPI, regulatory lag, mar-
keting). Geographical demand patterns (retail markets, location
patterns).
4. Static Equilibrium and Merger Analysis.
 The Cournot and Bertrand Models: Estimation and Identication
Problems.
 Alternatives to static Bertrand and Cournot; the \Conduct" pa-
rameter.
 Strategic Complements and Strategic Substitutes.
 Static Merger Models
 The Merger Guidelines, \standard" empirical analysis, and dy-
namic problems with the conclusions.
5. Dynamic Lessons from Two Period Models.
 Kreps and Scheinkman, Judd; quantities, prices or both.
 Mankiw and Whinston, over-investment?
 Some notes on \knowledge" versus \physical" capital,
 Lippman and Rumelt; implications of uncertainty.
 Dixit, entry deterrence.
 Sutton, Concentration and Market Size.
 Product Choice, Product Location, and Variety models.
 Empirical entry models; Berry, Bresnahan and Reiss.
 Entry models and product development. Theory and empirical
work.
2
6. Single Agent Dynamics.
 An (almost) standard investment example. The contraction map-
ping theorem and some of its corollaries, Blackwell's theorem.
 Theoretical examples
{ A monopolist with unknown demand,
{ Dixit's entry and exit (S-s) problem.
 Problem set: computing Dixit's policies and using them for infer-
ence.
 Empirical Examples
{ Timmins on regulation and natural resources,
{ Pakes on renewing patents,
{ Rust on machine replacement.
7. Multiple Agent Dynamics
 A review of some \competitive" dynamic models with heteroge-
neous agents.
 Markov Perfect Equilibrium. The Maskin-Tirole articles; entry
deterrence, kinked demand curves, wars of attrition, and linear
quadratic games.
 Judd on mergers, and on quantity and price setting.
8. A Computable Markov Perfect Framework and Numerical Analysis.
 Ericson-Pakes and Pakes-McGuire. A computational framework.
 Problem set: Computing and analyzing an equilibrium.
 Applied examples
 Computational problems and an outline of more advanced com-
putational techniques.
9. Extending the Simple Markov Perfect Model.
 Dynamic policy equations for single agent models when price (or
quantity) aects more than current prots.
3
 Dynamic policy equations for mutliple agent models when future
demand or cost functions depend on current price (or quantity)
decisions
 Applications and policy implications; learning by doing, durable
goods, experience goods, addiction, \network" externalities and
lock-in.
 Allowing for mergers.
10. Collusion
 An overview on issues, the law, and empirical work.
 Collusion in repeated games with and without asymmetric infor-
mation; Stigler, Friedman, Green and Porter, and Abreu Pearce
and Stachetti.
 The Rotemberg-Saloner model and extensions.
 Collusion in dynamic games; Davidson and Deneckre, Fershtman
and Pakes.
11. Technological Change.
 Diusion; aggregate and micro models.
 Knowledge spillovers and their likely importance.
 Markov Perfect Models with spillovers.
 Intellectual property; the institutional environment.
 Empirical work; a review of micro data sources and empirical re-
sults.