A guide to economics, statistics and finance that explores the
mathematical foundations underling econometric methods
An Introduction to Econometric Theory offers a text to help in the
mastery of the mathematics that underlie econometric methods and
includes a detailed study of matrix algebra and distribution theory.
Designed to be an accessible resource, the text explains in clear
language why things are being done, and how previous material informs a
current argument. The style is deliberately informal with numbered
theorems and lemmas avoided. However, very few technical results are
quoted without some form of explanation, demonstration or proof.
The author -- a noted expert in the field -- covers a wealth of topics
including: simple regression, basic matrix algebra, the general linear
model, distribution theory, the normal distribution, properties of least
squares, unbiasedness and efficiency, eigenvalues, statistical inference
in regression, t and F tests, the partitioned regression, specification
analysis, random regressor theory, introduction to asymptotics and
maximum likelihood. Each of the chapters is supplied with a collection
of exercises, some of which are straightforward and others more
challenging. This important text:
- Presents a guide for teaching econometric methods to undergraduate and
graduate students of economics, statistics or finance
- Offers proven classroom-tested material
- Contains sets of exercises that accompany each chapter
- Includes a companion website that hosts additional materials, solution
manual and lecture slides
Written for undergraduates and graduate students of economics,
statistics or finance, An Introduction to Econometric Theory is an
essential beginner's guide to the underpinnings of econometrics.
