Econometrics
Published on 1. April 2004
Book
Mixed media product
576 pages
978-0-07-110541-5 (ISBN)
Description
Stephen Schmidt is a superb and dedicated professor at a very good, liberal arts college, (Union in Schenectady, NY). After obtaining a PhD in Economics from Stanford University and teaching for 8 years, he has now written the book he has always wanted to write and use - an econometrics book that excites and motivates students about the value of statistical analysis in economics and gives them all of the tools they will need to do this analysis themselves. The goal of this book is to show students that econometric analysis is the bridge that connects economic theory with economic policy.
More details
Language
English
Place of publication
London
United States
Publishing group
McGraw-Hill Education - Europe
Dimensions
Height: 238 mm
Width: 190 mm
Thickness: 22 mm
Weight
889 gr
ISBN-13
978-0-07-110541-5 (9780071105415)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Schmidt
Econometrics with Data CD
Book
04/2004
Irwin Professional Publishing
€114.87
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Content
Part 1: Econometric AnalysisChapter 1 IntroductionChapter 2 Designing an econometric projectPart 2: Probability and StatisticsChapter 3 Random variablesChapter 4 EstimationChapter 5 Hypothesis testingPart 3: Linear RegressionChapter 6 Least Squares RegressionChapter 7 Properties of the least squares estimatorChapter 8 Multivariate regressionPart 4: Topics in Linear RegressionChapter 9 Selecting a Functional FormChapter 10 Determining the econometric specificationChapter 11 Instability of the regression equationPart 5: Violations of the Regression ModelChapter 12 AutocorrelationChapter 13 HeteroskedasticityChapter 14 Estimating multiple equationsPart 6: Advanced TopicsChapter 15 Endogenous variablesChapter 16 ForecastingChapter 17 Time series analysisChapter 18 Nonlinear modelsChapter 19 Dummy dependent variablesChapter 20 General discrete choice models