Abstract

This book interweaves inferential approaches and theory and practice in econometrics. Basic statistical and linear algebra concepts are introduced as they are needed to give life to the statistical model under study. Most econometric applications start with a tentative theory or hypothesis a sample of data and the goal of learning something about the phenomena under study from the limited set of observations. Therefore a sample of data that may be used to investigate a particular economic hypothesis is presented to motivate the analysis of each of the statistical models presented. This linkage between the economic process that is thought to have generated the data and a particular statistical model is a unifying theme throughout the book. It progresses from the special case of investigating the possibilities for determining the location and scale parameters for a population from a sample of observations to investigating a complex simultaneous system of structural equations under general stochastic assumptions. To ensure that the reader understands the basic concepts and conclusions as they relate to linear statistical models simple special case models are evaluated and then the analysis is repeated for the general case. The 1st half of book gives the student a solid introduction to the formulation and use of linear statistical models. The 2nd half introduces the student to the econometric problems that arise when it is taken into account that economic data are stochastic dynamic and simultaneous and that the optimal statistical procedure sometimes changes as we change the statistical model the amount and type of information used and the measure of performance.

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