In recent years there have been remarkable improvements in methods of inference in general and in econometric and statistical methods of inference in particular. These developments came together with an increase in available data and information. Some of these data sets are very large, while others are small, but since most of these data are non-experimental and quite blurry, none of these data sets are perfect. Nonetheless, most currently-used theoretical and empirical methods in the social, behavioral, decision and natural sciences fail to adequately take these information limitations into account. Ideally a model should use all available information and then use a consistent and efficient method of inference. There is a critical need for new approaches to modeling and inference that can handle limited, inaccurate, or constantly evolving information. Classical econometrics and statistics, for example, are built on a set of assumptions that are often not verifiable (say, a pre-specified likelihood) or unobservable. Different methods to analyze and to better understand imperfect data are evolving constantly. Many of these developments are either too new or too specialized to fit within the traditional university course framework.
The primary purpose of the summer program in Info-Metrics is to provide students, researchers and faculty with state of the art hands-on tutorials and training workshops on inferential methods for analyzing data and processing information across the sciences. Examples include info-metrics, Bayesian methods of inference, Information-Theoretic methods of estimation, generalized method of moments, nonparametric methods, forecasting, financial econometrics, agent based models, computational methods in the social sciences, micro-econometrics and panel data methods, Bayesian decision making, statistical model selection, and more.
Each day of the training workshop consists of morning tutorial that develop the basic concepts and philosophy as well as their applications to real world problems and data. Each afternoon, these methods will be applied and practiced in the computer lab. These daily tutorials and work in the computer lab provide the participants with “hands on” experience in using these methods with real data.
Past instructors and workshop facilitators include: Amos Golan, John Geweke, Bill Greene, Alastair Hall, John Rust, Eric Zivot, Graham Elliott and Ingmar Prucha.
Since 2005, every year during the summer, Info-Metrics Institute tutorials are offered at American University.
Target Group and Requirements
Each course/workshop in this program is open to participants who have completed at least a year of econometrics/statistics at the PhD level. These training workshops are of interest to graduate students, data analysts, research scientists, professional economists, researchers and econometricians/statisticians who work in government agencies, non-governmental organizations and in the private market.
Individuals that take the courses for credit receives 3 credit per course.
Each participant that completes a tutorial receives a Certificate of Completion.
The text for each training-workshop will be announced prior to the workshop and will include a text book and/or a reader consisting of a collection of papers.
Tutorials begin at 9:00 am and end at 4:30 or 5:00 pm. There will be a morning coffee break, a lunch break and an afternoon break.
Registration for Non-credit
ECON-096 N91 Nonparametric Kernel Methods (meets M-Fri from 9 to 5)
ECON-096 N92 Interdisciplinary Apps Micro (meets T-Sat from 9 to 5)
Registration for credit
ECON-696-N01 Nonparametric Kernel Methods (meets M-Fri from 9 to 5)
ECON-696-N02 Interdisciplinary Apps Micro (meets T-Sat from 9 to 5)
AU graduate students may register beginning 1 April through myAU portal after getting authorization from your advisor.
Nondegree/Visiting graduate students may register beginning 1 April by submitting the Nondegree Summer Enrollment Form online here. Once you submit this form, you will be registered (if space is available). You should expect confirmation and more information from the Registrar's Office. http://www.american.edu/summer/summer-visiting.cfm
If you are admitted to any of the Washington DC area schools and plan to transfer credit, please be sure to register through your school's Consortium Coordinator or Registrar's Office. http://www.consortium.org/
Info-Metrics Institute, American University, Kreeger Hall 104
4400 Massachusetts Ave., NW, Washington, DC 20016-8029
Phone: 202-885-3770 Fax: 202-885-3790 firstname.lastname@example.org
Nonparametric Kernel Methods for Practitioners Across the Sciences
May 18-22, 2015
Instructor: Jeffrey S. Racine, Senator William McMaster Chair in Econometrics; Professor, Department of Economics, Professor, Graduate Program in Statistics, Department of Mathematics and Statistics, McMaster University
Location: Info-Metrics Institute, American University
Class Topics: Kernel methods from A to Z with labs in R so that participants leave with the ability to deploy the methods on their own data.
Interdisciplinary Applications of Microeconometrics
May 26-30, 2015
Instructor: William H. Greene, Robert Stansky Professor of Economics and Statistics, Stern School of Business, New York University
Location: Info-Metrics Institute, American University
Class Topics: Methods of Estimation and Inference: Parametric and Semiparametric Regression, Maximum Likelihood, Simulation, Nonlinear Modeling for Continuous and Discrete Choice for Cross Section and Panel Data, Applications from Health Economics, Transport, Entertainment, and Production/Efficiency and Productivity.
Information and Entropy Econometrics—Theory and Practice
May 16 - 20, 2005
Amos Golan, American University Class Syllabus
Information Theoretic and Entropy Econometrics
Amos Golan, American University Class Information
Amos Golan, George G. Judge, Douglas Miller (1996), Maximum Entropy Econometrics: Robust Estimation with Limited Data, John Wiley & Sons. (Link to Publisher's Website)
A printed and bound version of this article is available at a 50% discount from Now Publishers. This can be obtained by entering the promotional code MC08004 on the order form at Now Publishers. You will then pay $45/Euro plus postage.
Bayesian Econometrics & Decision-Making
Instructor: John Geweke,
U of Iowa and UTS, Sydney, Australia Course Description
Info-Metrics: Theory and Practice
Instructor: Amos Golan, American University
Spatial Econometrics: Theory and Practice
Instructor: Ingmar Prucha, Professor, Department of Economics at University of Maryland College Park
Microeconometrics with focus on Panel Data and Discrete Choice: Theory and Practice
May 14-18 (Monday-Friday), 2012
Instructor: William Greene (NYU)
Location: Info-Metrics Institute, American University Class Information