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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 Â鶹ÊÓƵ.

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)

Â鶹ÊÓƵ graduate students may register beginning 1 April through myÂ鶹ÊÓƵ portal after getting authorization from your advisor.

Nondegree/Visiting graduate students may register beginning 1 April: see Â鶹ÊÓƵ 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, Â鶹ÊÓƵ, 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, Â鶹ÊÓƵ
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, Â鶹ÊÓƵ
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, Â鶹ÊÓƵ

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, Â鶹ÊÓƵ

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, Â鶹ÊÓƵ >

A Special Two-Day Tutorial on Info-Metrics

July 9-10 (Monday & Tuesday), 2012
Instructor: Amos Golan (American U)
Location: Info-Metrics Institute, Â鶹ÊÓƵ
Class Information

2011 Classes

Info-Metrics: Theory and Practice

Instructor: Amos Golan, Â鶹ÊÓƵ

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, Â鶹ÊÓƵ

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® 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, Â鶹ÊÓƵ
Class Syllabus