The small sample properties of estimators and tests are frequently
too complex to be useful or are unknown. Much econometric theory is
therefore developed for very large or asymptotic samples where it
is assumed that the behaviour of estimators and tests will
adequately represent their properties in small samples. Refined
asymptotic methods adopt an intermediate position by providing
improved approximations to small sample behaviour using asymptotic
expansions. Dedicated to the memory of Michael Magdalinos, whose
work is a major contribution to this area, this book contains
chapters directly concerned with refined asymptotic methods. In
addition, there are chapters focusing on new asymptotic results;
the exploration through simulation of the small sample behaviour of
estimators and tests in panel data models; and improvements in
methodology. With contributions from leading econometricians, this
collection will be essential reading for researchers and graduate
students concerned with the use of asymptotic methods in
econometric analysis.
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