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Abstract Details
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Activity Number:
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534
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Type:
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Roundtables
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Date/Time:
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Wednesday, August 3, 2011 : 12:30 PM to 1:50 PM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #300693 |
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Title:
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Rich-Data Problems in Econometrics
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Author(s):
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Hyunyoung Choi*+
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Companies:
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Google Inc.
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Address:
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1600 Amphitheatre parkway, Mountain View, CA, ,
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Keywords:
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Variable selection ;
Factor regression for forecasting ;
Large Vector Autoregressions
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Abstract:
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Rich-data problems are becoming commonplace in many areas of sciences such as molecular biology and evolution, environment and climate modeling and forecasting, to name a few. The same trend is observed in econometrics, particularly in macroeconomics and financial econometrics. Such rich-data environments have posed challenging and computationally expensive obstacle to direct implementation of standard statistical tools through all steps of modeling, i.e. data processing, statistical inference and summary and forecasting. In this roundtable we will talk about such difficulties, learn how applied econometricians are tackling them.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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