Contact Us
Info-Metrics Summer Program
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.
Objective
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.
The Program
Since 2005, every year during the summer, Info-Metrics Institute tutorials are offered at 小蓝视频.
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.
Credits
Individuals that take the courses for credit receives 3 credit per course.
Certificates
Each participant that completes a tutorial receives a Certificate of Completion.
Workshop Material
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.
Daily Schedule
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
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)
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)
小蓝视频 graduate students may register beginning 1 April through my小蓝视频 portal after getting authorization from your advisor.
Nondegree/Visiting graduate students may register beginning 1 April: see 小蓝视频 Nondegree Student information for more details.
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 Coordinator or Registrar's Office.
Check out the schedule of classes.
For further information, please contact:
Info-Metrics Institute, 小蓝视频, Kreeger Hall 104
4400 Massachusetts Ave., NW, Washington, DC 20016-8029
Phone: 202-885-3770 Fax: 202-885-3790
info-metrics@american.edu
Past Classes
2015 Classes
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, 小蓝视频
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, 小蓝视频
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.
2013 Classes
A Special Two-Day Tutorial on Info-Metrics
May 28 & 29 (Tuesday and Wednesday), 2013
Instructor: Amos Golan (American U)
Location: Info-Metrics Institute, 小蓝视频
2012 Classes
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, 小蓝视频
Data Mining and Information: Theory and Practice
May 29-June 2 (Tuesday-Saturday), 2012
Instructors: Teddy Seidenfeld (Carnegie Mellon U), Richard Scheines (Carnegie Mellon U), Kevin Zollman (Carnegie Mellon U) Location: Info-Metrics Institute, 小蓝视频 >
A Special Two-Day Tutorial on Info-Metrics
July 9-10 (Monday & Tuesday), 2012
Instructor: Amos Golan (American U)
Location: Info-Metrics Institute, 小蓝视频
Class Information
2011 Classes
Info-Metrics: Theory and Practice
Instructor: Amos Golan, 小蓝视频
Spatial Econometrics: Theory and Practice
Instructor: Ingmar Prucha, Professor, Department of Economics at University of Maryland College Park
2010 Classes
Forecasting
Instructor: Graham Elliott, UCSD
Bayesian Econometrics & Decision-Making
Instructor: John Geweke,
U of Iowa and UTS, Sydney, Australia
2009 Classes
Financial Econometrics and Volatility Models
Eric Zivot
Discrete Choice
William Greene, NYU
2008 Classes
Information Theoretic and Entropy Econometrics
Amos Golan, 小蓝视频
Amos Golan, George G. Judge, Douglas Miller (1996), Maximum Entropy Econometrics: Robust Estimation with Limited Data , John Wiley & Sons. ( Link to Publisher's Website)
Additional Material:
A. Golan, " Information and Entropy Econometrics - A Review and Synthesis", Foundations and Trends庐 in Econometrics: Vol. 2: No 1-2, pp 1-145. ( Book Information)
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.
Computational Economics
John Rust
Class Information
Note: Includes agent-based modeling and programming.
2007 Classes
Generalized Method of Moments-Theory and Practice
May 14 - 18, 2007
Alastair Hall, North Carolina State University and University of Manchester
Class Information
Panel Data
May 29 - June 2, 2007
William Greene, NYU
2006 Classes
Bayesian Econometrics and Decision-Making
May 15 - 19, 2006
John Geweke, University of Iowa
Class Information
Discrete Choice Modeling
May 30 - June 3, 2006
William Greene, NYU
Class Information
2005 Classes
Information and Entropy Econometrics-Theory and Practice
May 16 - 20, 2005
Amos Golan, 小蓝视频
Class Syllabus