Ramanathan, Ramu : University of California-San Diego
Summary
Statistical Methods in Econometrics is appropriate for beginning graduate courses in mathematical statistics
and econometrics in which the foundations of probability and statistical theory are developed for application to
econometric methodology. Because econometrics generally requires the study of several unknown parameters, emphasis
is placed on estimation and hypothesis testing, involving several parameters. Accordingly, special attention is
paid to the multivariate normal and the distribution of quadratic forms. Lagrange multiplier tests are discussed
in considerable detail, along with the traditional likelihood ratio and Wald tests. Characteristic functions and
their properties are fully explored. Also asymptotic distribution theory, usually given only cursory treatment,
is discussed in detail. The book assumes a working knowledge of advanced calculus (including integral calculus),
basic probability and statistics, and linear algebra. Important properties from matrix algebra are summarized in
the appendix. Numerous examples, exercises, and practice problems are included.
Covers both mulitvariate analysis and matrix algebra.
Focuses on newer tests of hypotheses such as the Lagrange multiplier test.
Discusses characteristic functions in depth.
Material has evolved during 15 years of classroom instruction.
Table of Contents
Probability Theory: Introduction.
Basic Probability.
Random Variables and Distributions.
Some Special Distributions.
Multivariate Distributions.
Statistical Inference: Sampling Theory.
Asymptotic Distribution Theory.
Estimation.
Tests of Hypothesis.
Econometrics: Multiple Regression.
Functional Forms and Dummy Variables.
Nonspherical Distrubances.
