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Title: Amos Golan, Info-Metrics Institute and Economics, American University; External Professor, Santa Fe Institute; Senior Associate, Pembroke College, Oxford
Sharing: Public
Start Time: Thursday September 06, 2018 02:30 PM
End Time: Thursday September 06, 2018 03:45 PM
Location: Ballantine Hall  
Contact: Jon Michael Dunn
Url: http://info-metrics.org/
Free/Busy: busy
Description:

Economics Department (Econometrics Group)

Speaker:   Amos Golan, Info-Metrics Institute and Economics, American University;  External Professor, Santa Fe Institute; Senior Associate, Pembroke College, Oxford

Where:  Ballantine Hall, Rm. 003

Where:  Thursday, September 6, 2018, 2:30 - 3:45 pm

Topic: Model Misspecification: Classical Statistics vs. Info-Metrics

ABSTRACT

With imperfect and incomplete information, it is quite common to misspecify a model. This problem exists not only in the social and behavioral sciences, where the underlying models are often a mystery, but also in the other sciences. Traditionally, misspecification deals with the basic issues of model selection (such as the choice of the functional form, moment specification, etc.), variable selection, and frequently the choice of likelihood or the choice of the statistical inferential method itself. Within the info-metrics framework – the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information – misspecification may appear in three ways. The first is to do with the specification of the constraints (the functional form used, based on the input information). The second is to do with the choice of the criterion or decision function. Whether specified correctly or not, together they determine the solution. The third is to do with priors’ misspecification. In this talk, I am concerned with the first two fundamental misspecifications: the constraints and the criterion. (Note, however that the empirical problem of variable selection for a specific model is similar across all inferential methods, so I do not discuss it here.)

In my talk, I will discuss the above misspecification issues and will contrast classical methods with info-metrics. I will demonstrate some of the main issues via a simple example where I investigate power law distributions using Shannon entropy and the Empirical Likelihood. I show that though they both yield the same prediction, one of them is misspecified. But which one?

My talk will be based on my new book ‘Foundations of Info-Metrics: Modeling, Inference, and Imperfect Information,’ http://info-metrics.org/ in which I develop and examine the theoretical underpinning of info-metrics and provide extensive interdisciplinary applications.

BIO: 

Amos Golan directs the Info-Metrics Institute at AU. His main area of research is information and the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information (Info-Metrics).   Golan is an External Professor, The Santa Fe Institute.  Golan is also a Senior Associate, Pembroke College, Oxford. 

   
Amos Golan's new book Foundations of Info-Metrics: Modeling, Inference, and Imperfect Information is now available from Oxford University Press

 

See Also 'Foundations of Info-Metrics' (Book)
'Foundations' Book - Web Support
Info-Metrics Institute
Economics Department

Poster

 

Contact Email: dunn@indiana.edu
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