Kiefer's interest in combining theoretical economics and statistics
has led to structural empirical models in a number of fields.
His early work on program evaluation proposed methods of sorting out
employment effects from wage effects of training in determining earnings.
This was followed in joint work with George Neumann by the first structural
estimation of job search models of the labor market. This was
followed up by research on specification and estimation of equilibrium
search models, in work with Neumann, B.J. Christensen and others. In
finance, Kiefer has estimated models of market microstructure, with
special emphasis on the roles of information and liquidity in determining
price adjustments. The PIN statistic invented in this work, an
estimate of the probability of an informed trade, is now in wide use
in empirical finance. This work was joint with David Easley and Maureen O'Hara. Derivative
pricing and the incorporation of options data in estimating financial
models is the topic of joint work with Christensen. Theoretical
work on the optimal accumulation and valuation of information (partially
joint with Easley, Nyarko, and Bala)
showed that full information accumulation is not always optimal and
provided guidance for optimal experimentation. Current work in finance
includes specification and evaluation of credit scoring models, estimation
of default probabilities for financial institutions and portfolio risk
measurement and management.