Spring 2015
Course Listings (PHD)
= Cancelled |
= New Class Added |
= Professor Change |
= Rescheduled (day/time change) |
Accounting/Taxation
-
ACCT-GB.4320 Empirical Research in Financial Accounting III (3)
Course Description:
This course explores analytical models both in the financial and in the managerial accounting literature. The format is highly interactive; students study assigned papers in depth and present them in class. Analytical research design issues are emphasized. The linkages between the analytical models and the testing of their implications are elucidated. In this context, occasional empirical papers that test well-articulated analytical models' implications are also discussed.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
M
10:30 am
- 1:00 pm
|
02/02-05/11 |
Lev,B |
meets in Acctng conf room |
Economics
-
ECON-GB.3332 Advanced Topics in Macroeconomics (Macroeconomics II) (3)
Course Description:
This course is intended for Ph.D. students who already have substantial prior preparation in dynamic macroeconomics. The objective is to talk about research and potential dissertation topics. Most of the topics fall under the general description of dynamic general equilibrium theory. In recent years, the topics have included financial markets and the growth of firms; optimal monetary policy; dynamic contracting; asset pricing; business cycles; and labor markets. Students are expected to present their own work at the end of the course.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
|
02/02-05/11 |
Ruhl,K |
PhD students only |
-
Course Description:
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 causal inference.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
|
02/02-05/11 |
Kawai,K |
PhD students only |
Finance
-
Course Description:
We shall study the main models of behavioral economics and finance. We will discuss the empirical evidence, but we emphasize the models&especially the novel, promising approaches, rather than a review of past successes. Topics will include: bounded rationality, inattention, imperfect understanding of probabilities, narrow framing, sparse dynamic programming, and more specialized finance models: limits of arbitrage, loss aversion in stock trading, under and over reaction, extrapolation and categorical thinking.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
W
3:00 pm
- 5:50 pm
|
04/01-05/06 |
Gabaix,X |
PhD Students only |
-
Course Description:
This is the third course in the theory of financial decision making. The first half of this course deals with issues in corporate finance. Topics include agency theory, signaling and asymmetric information models, taxes, dividends, and capital structure. The second half of the course focuses on the pricing of options, futures, and other derivative securities instruments.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
M
3:00 pm
- 5:50 pm
|
02/02-05/11 |
Gabaix,X/Schnabl,P |
PhD Only |
Information Systems
-
Course Description:
This course introduces students to scientific paradigms and research perspectives related to the economics of information technologies. Topics in 2012 include information goods, piracy, digital rights management, network economics, sponsored search auctions, user-generated content, contagion in networks, technological innovation, IT productivity, the digital commons and online privacy.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
T
09:30 am
- 12:30 pm
|
02/03-05/05 |
Sundararajan,A |
PhD Students only |
Interarea
-
Course Description:
This is an intermediate level, Ph.D. course in the area of Applied Econometrics dealing with Panel Data. The range of topics covered in the course will span a large part of econometrics generally, though we are particularly interested in those techniques as they are adapted to the analysis of 'panel' or 'longitudinal' data sets. Topics to be studied include specification, estimation, and inference in the context of models that include individual (firm, person, etc.) effects. We will begin with a development of the standard linear regression model, then extend it to panel data settings involving 'fixed' and 'random' effects. The asymptotic distribution theory necessary for analysis of generalized linear and nonlinear models will be reviewed or developed as we proceed.. We will then turn to instrumental variables, maximum likelihood, generalized method of moments (GMM), and two step estimation methods. The linear model will be extended to dynamic models and recently developed GMM and instrumental variables techniques. The classical methods of maximum likelihood and GMM and Bayesian methods, expecially MCMC techniques, are applied to models with individual effects. The last third of the course will focus on nonlinear models. Theoretical developments will focus on heterogeneity in models including random parameter variation, latent class (finite mixture) and 'mixed' and hierarchical models. We will also visit the theory for techniques for optimization in the setting of nonlinear models. We will consider numerous applications from the literature, including static and dynamic regression models, heterogeneous parameters models (e.g., Fama-Macbeth), random parameter variation, and specific nonlinear models such as binary and multinomial choice and models for count data.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
TR
1:00 pm
- 2:30 pm
|
02/03-05/07 |
Greene,W |
PhD Students only |
Management and Organizations
-
Course Description:
Organizations operate in dynamic environments. This course introduces doctoral students to the principal theoretical perspectives and empirical findings used to explain relationships among environments, organizational strategies, designs, and performance. Students are expected to develop expertise in the analysis of environments and organizations from several theoretical perspectives, such as resource dependence theory, institutional theory, organizational ecology, and industrial organization economics. The seminar stresses the competitive and mutual dimensions of environments that propel managers to enact business, corporate, and collective strategies, structures, processes, and systems to enhance their firms' effectiveness. Both theoretical and empirical research are examined to illustrate how different theoretical perspectives require different empirical research methodologies.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
W
5:00 pm
- 8:00 pm
|
02/04-05/06 |
Greenberg,J |
PhD Students only |
-
Course Description:
The field of Strategy is motivated by a simple question: "What allows certain firms to earn positive economic profits while others deliver negative returns?" It offers a set of complicated answers: differences in industry structure, internal capabilities, superior managerial decision making, vertical and horizontal scope and so on.
In the past 3 decades, Strategy has emerged as an important area of study in Management. The Business Policy and Strategy division now boasts of the largest membership in all of AOM. In practice, the field of Strategy is the only area that speaks exclusively to the highest level of corporations - the leaders, the CEOs, and the movers and shakers of the modern firm. It transcends functional areas such as finance or marketing, as it brings functional knowledge to bear on the most critical issues faced by the firm's key decision makers.
While there is a strong degree of core consensus among scholars, Strategy is a young discipline with many unresolved theoretical puzzles and empirical challenges. Far from being obstacles, these gaps present attractive and ample opportunities for fledging scholars to make a mark. Whether you aspire to contribute directly to the scholarship of Strategy or are simply curious about how Strategy may relate to your area (whether it be Information Systems, Marketing or Public Policy), this course offers an overview of classic concepts and ideas and introduce you to current research in Strategy.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
|
02/02-05/11 |
Schilling,M |
PhD Students only |
Marketing
-
Course Description:
The first part of this course covers communication and public policy issues in consumer behavior. It examines recent theory and research bearing on how communications and situational factors affect consumer behavior. In the process, students also become familiar with some related public policy issues, including deceptive and corrective advertising, and trademark-related matters. The second part of the course introduces students to behavioral decision research. Topics covered include judgment under uncertainty, risk taking, and conflicting values.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
T
2:30 pm
- 5:30 pm
|
02/03-05/05 |
Morwitz,V |
PhD Students only |
-
Course Description:
This course is intended as an introduction for PhD students who want to design and analyze behavioral experiments. The course has three objectives: to learn how to test research ideas with rigorous, unconfounded experimental designs, to learn how to analyze these designs (using SAS), and to learn how to interpret and evaluate experimental work by other researchers. The topics covered include between subjects, within-subject, and mixed designs, factorial designs, and analysis of covariance. Please keep in mind that this course is not a statistics course. While we will cover some of the calculations behind the analyses, the emphasis is on learning to use the techniques and interpreting applications.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
W
2:00 pm
- 5:00 pm
|
02/02-05/11 |
Meyvis,T |
PhD Students only |
Operations Management
-
Course Description:
This Doctoral course will serve as an introductory course to stochastic processes. We will closely follow the book "Stochastic Processes" by Ross. The course will begin with a one week review of basic concepts in probability and then proceed to the study of Poisson processes, renewal processes, discrete time Markov chains, and finally, continuous time Markov chains. The are no prerequisites for the course, however, a calculus based understanding of probability is helpful. Courses in analysis and measure theory are not required. A tentative course outline is as follows.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
M
2:00 pm
- 5:00 pm
|
02/02-05/11 |
Reed,J |
PhD Students only |
Statistics
-
Course Description:
Frequency Domain Time Series is an advanced course on foundations and applications of time series. Methods involving periodograms and spectral densities are emphasized. Linear filtering and spectral representations (stochastic integrals)for stationary time series are used as unifying themes. The second half of the course considers GARCH models, fractals, long memory and fractional cointegration. Again, emphasis is on insights gained from the frequency domain viewpoint.
The mathematics used in the course is Fourier analysis, a useful tool for all technically-oriented students. All mathematical results are presented in a self-contained manner.
The course grades are based on homework assignments (70% of the grade)and an in-class open-book final exam (30% of the grade). Homeworks can be re-submitted for further credit, at any time.
There is a clear need for advanced students in statistics, finance and economics to have a deep understanding of time series in the frequency domain. Increasingly, frequency domain methods and models are being used by practitioners.
Section |
Meeting Times |
Dates |
Instructor |
Notes |
20 |
T
1:00 pm
- 4:00 pm
|
01/27-05/05 |
Hurvich,C |
By Permission for nonPhDs |
|