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Nicholas
M. Kiefer |
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Nicholas
M. Kiefer works primarily in econometrics and statistics with applications
in financial economics, credit scoring and risk management in banking,
consumer trend forecasting, and development of quantitative management
techniques. Previously, Kiefer worked on developing structural job search
models and subsequently equilibrium search models. His work on the value
of information, using a dynamic programming framework, led to results
on the possibility and potential optimality of learning. Subsequent
theoretical and empirical work on market microstructure led to invention
of the PIN, a widely used statistic for measuring the information content
of trades. Recently, Kiefer has developed a new approach to asymptotic
approximations for use in testing problems in dynamic models. Most recently,
Kiefer is developing methods for inference about small probabilities,
with special interest in banking applications and the formal incorporation
of expert information using Bayesian techniques. Details are given
in the Research Summary. The unifying theme
of the work is the complementary use of statistics and economic theory.
Both statistical modeling and theoretical modeling are seen as tools
to summarize and focus information. Theory and econometrics are
treated as similar, complementary activities, not separate fields. This
view is reflected in the new book with B.J. Christensen
Economic Modeling and Inference. |
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